Mittwoch, 15. Oktober 2014

Measuring the Sense of Community in Online Communities

A strong sense of community (SOC) is considered to be desirable because it fosters pro-social behavior of community members and helps deal with external challenges/threats (cf. Sense of community in virtual communities). So every community manager should be highly interested in assessing the SOC of her/his community. But measuring the SOC and interpreting the result is by no means easy.

Sense of Community: Face-to-face communities vs. online communities

Originally, the SOC-concept was developed for face-to-face communities (geographical neighborhoods). McMillan and Chavis (1986) [1] suggest four dimensions which work together dynamically in order to create and maintain an overall sense of community:

1. Membership [MEM]: The concept includes emotional safety derived from membership, the sense of belonging and identification with the community, personal investment in the community leading to stronger bonds, and some kind of common symbol system, which unites a community. These attributes go together in a mutually self-reinforcing way.

2. Influence [INFL] means a reciprocal relationship between individuals and the community in terms of their impact on one another. Influence is a bi-directional concept, as for a group to be attractive, an individual must feel they have some control and influence over it, while, on the other hand, for a group to be cohesive it must also influence its individual members. McMillan and Chavis (1986) state that pressure of conformity from community members actually comes from the needs of individual members for consensual validation. In turn conformity serves as a force for cohesiveness.

3. Integration and Fulfillment of Needs [IFN]: Members must perceive the association to the community as rewarding for the individual (like status of membership, or the possibility to share in the success of the community, and the perceived competence of other individuals in the community who might help the member with her/his own issues).

4. Shared Emotional Connection [SEC]: The more people interact, the more likely they are to form close relationships. The more positive this interaction, the stronger the bond developed.

SOC soon became an important enabler for the success of face-to-face communities. It was said to
  • increase participation and feelings of belonging, 
  • hold community development efforts together,  
  • lead to satisfaction with and commitment to the community, 
  • enhance involvement and problem focused coping behavior, 
  • have a positive impact on the sustainability of a community  
  • lead to higher satisfaction, participation, and commitment within social structures (cf. [10] for the relevant literature). 
In 2002, Obst et al. [1a] published the results of their investigation about the sense of community (cf. Sense of community - Is there a fifth dimension?) They had asked 359 members of SF fandom attending Aussiecon 3, the 1999 World Science Fiction Convention how they feel about the fandom community (a - relational - community of interest with membership from all over the world) and about their neighborhood (a geographical community). McMillan and Chavis' four dimensions of SOC could be established in both communities (SF fandom and neighborhood). BUT: In-group identification was a separate 5th dimension in both community types.
All five dimensions were significant predictors of overall sense of community in both community types but acted differently with respect to the community type:
  • Conscious identification with fandom emerged as the strongest predictor, while in the neighborhood setting it was the weakest predictor.
  • Belonging was a strong predictor in both communities. This suggests that belonging is an important dimension of sense of community in whatever context we are examining.
  • Identification, however, seems to be more important in the communities to which we choose to belong than in those communities which we may have made a less conscious decision to join.
  • Influence was an important predictor in geographical communities, however not at all important in the interest community. This may again be due to the element of perceived choice. If you choose to belong to an association due to common interest the need for influence over that association may be less than the need to feel some control or influence over the area in which you live. 
Another researcher, Anita Blanchard [8], too, had found a considerable overlap between the senses of community for face-to-face and virtual communities, but there were also significant differences (cf. Sense of virtual community: Antecedents and consequences for community management):
  • Influence may be less important to members in online communities than to members of face-to-face communities. (Note: Koh & Kim [8], on the other hand, stress the importance of influence in online communities, cf. Sense of community - an alternative approach).
  • Additionally, members in online communities feel that they know the personalities of others and experience and observe more personal relationships than do members of face-to-face communities.
Thus, there seem to be important differences between the sense of community in virtual communities (SOVC) and the sense of community in face-to-face communities (SOC). Using the same tool for measuring the sense of community in both communities may not be rewarding.

Measuring the SOC - The Sense of Community Index (SCI)

One tool for measuring the SOC in face-to-face communities is the Sense of Community Index (SCI) which is said to be the most widely used measure of the construct. It was developed as part of the seminal New York City Block Booster action-research project. [2] The scale items are published in the appendix of Perkins et al. (1990). [3].

Unfortunately, there was never a confirmation of its intended dimensions or sub scales measuring the four aspects of SOC (MEM, INFL, IFN, SEC). Several studies tried to find out which item measured which aspect of SOC. The results are in the table. Item #10 (It is very important to me to live on this particular block.) for example "somehow" measures all four aspects, depending on the community under study.

Table: Comparison of factor structure found across studies [6]
*) Original: resident survey data from 47 street blocks in five neighborhoods in Brooklyn and Queens, New York (1985 - 1986)
**) Obst et. al: geographical community data
***) Chipuer & Pretty: adult neighborhood data
****) Obst & White: university students' community, two items removed because not applicable

Blanchard's SOVC - an adaption of the original SCI

Based on her prior findings, Anita Blanchard [7] developed a sense of virtual community (SOVC) measure, on the basis of the SCI. Given the differences between face-to-face communities, there may be items in the SCI that do not have relevance in virtual communities, and the SCI may be missing parts of the SOVC. The questionnaire had 22 items; four items from the SCI had to be eliminated because they were inappropriate. The resulting 18 items in the SOVC measure are evenly divided between the SCI and newly developed measures. The newly developed items were introduced in order to assess support and identification. The SOVC had a Likert type response set (1 = never to 4 = quite a lot), whereas the SCI had a true-false response set.
Items adapted from the original SCI
  • Q1. I think this group is a good place for me to be a member.
  • Q3. Other members and I want the same thing from this group.
  • Q4. I can recognize the names most members in this group.
  • Q5. I feel at home in this group.
  • Q7. I care about what other group members think of my actions.
  • Q9. If there is a problem in this group, there are members here who can solve it.
  • Q10. It is very important to me to be a member of this group.
  • Q12. I expect to stay in this group for a long time.
Deleted during the analysis
  • Q2. Members of this group do not share the same values.
  • Q6. Very few other group members know me.
  • Q8. I have no influence over what this group is like.
  • Q11. Members of this group generally don’t get along with each other.
Additional items related to "support"
  • Q13. I anticipate how some members will react to certain questions or issues in this group.
  • Q14. I get a lot out of being in this group.
  • Q15. I’ve had questions that have been answered by this group.
  • Q16. I’ve gotten support from this group.
  • Q17. Some members of this group have friendships with each other.
  • Q18. I have friends in this group.
  • Q19. Some members of this group can be counted on to help others.
Additional items related to "identification"
  • Q20. I feel obligated to help others in this group.
  • Q21. I really like this group.
  • Q22. This group means a lot to me.
Interestingly, Blanchard circumvent the problem of attributing the items to different scales measuring different aspects of the SOVC, she measured an overall factor instead. The test in listservs and Usenet newsgroups ranging from pet lovers to human resource professionals showed that the 18-items SOVC questionnaire was a more sensitive measure than the SCI.

The Sense of Community Index 2 (SCI-2) © - a revision of the SCI [9]

In 2008, Chavis et al. [9] presented a revision of the SCI, a 24 item Sense of Community Index version 2 (SCI-2). The revised version comes with a Likert-scale response format (1 = not at all, 4 = completely) and was used in a survey with 1.800 people. Unlike SCI, it was able to cover all the attributes of a sense of community described in the original theory - but in a face-to-face community context. Here are the items:
Reinforcement of Needs
  • 1. I get important needs of mine met because I am part of this community.
  • 2. Community members and I value the same things.
  • 3. This community has been successful in getting the needs of its members met.
  • 4. Being a member of this community makes me feel good.
  • 5. When I have a problem, I can talk about it with members of this community.
  • 6. People in this community have similar needs, priorities, and goals.
Membership
  • 7. I can trust people in this community.
  • 8. I can recognize most of the members of this community.
  • 9. Most community members know me.
  • 10. This community has symbols and expressions of membership such as clothes, signs, art, architecture, logos, landmarks, and flags that people can recognize.
  • 11. I put a lot of time and effort into being part of this community.
  • 12. Being a member of this community is a part of my identity.
Influence
  • 13. Fitting into this community is important to me.
  • 14. This community can influence other communities.
  • 15. I care about what other community members think of me.
  • 16. I have influence over what this community is like.
  • 17. If there is a problem in this community, members can get it solved.
  • 18. This community has good leaders.
Shared emotional connection
  • 19. It is very important to me to be a part of this community.
  • 20. I am with other community members a lot and enjoy being with them.
  • 21. I expect to be a part of this community for a long time.
  • 22. Members of this community have shared important events together, such as holidays, celebrations, or disasters.
  • 23. I feel hopeful about the future of this community.
  • 24. Members of this community care about each other.
Abfalter at al. [10] tested a German version of the SCI-2 in an online community for elderly Germans (http://feierabend.de,  approximately 163k members as of May 2011, 312 respondents). Nine items of the SCI-2 had to be eliminated because they did not measure SOVC. However, the remaining 15 measures suggested a good fit of all four dimensions of the SOC. Here are the eliminated items:
Reinforcement of Needs
  • 2. Community members and I value the same things.
  • 3. This community has been successful in getting the needs of its members met.
  • 4. Being a member of this community makes me feel good.
Membership
  • 8. I can recognize most of the members of this community.
  • 10. This community has symbols and expressions of membership such as clothes, signs, art, architecture, logos, landmarks, and flags that people can recognize.
  • 11. I put a lot of time and effort into being part of this community.
  • 12. Being a member of this community is a part of my identity.
Influence
  • 15. I care about what other community members think of me.
Shared emotional connection
  • 22. Members of this community have shared important events together, such as holidays, celebrations, or disasters.
Responsible for this elimination are several particularities of the Feierabend-Community:
  • Community size: In a large community, members have little knowledge about each other. How should they know whether all other members value the same things? Furthermore, in a large community the members' needs and well-being are likely to vary enormously which may explain why item #3 and item #4 had to be dropped.
  • Members' motivation: In communities where getting a certain information is the members' primary concern, the individual member may not have to invest a lot of time and effort, which would explain the exclusion of item #11. But, if the questionnaire had been accidentally distributed solely among the community's core members the result might have been different.
  • Anonymity: The authors assume that anonymity is the main reason why so many items measuring the membership aspect of SOVC - in this study - did not measure SOVC significantly. For example, why should I care about what other community members think of me (item #15) if I can remain anonymous?
  • Community type: Some items (like item #10) are only applicable to face-to-face communities (or at least to virtual communities where members meet face-to-face on a regular basis like sci-fi fandom conventions).
Therefore, Abfalter et al. suggest to rephrase some of the eliminated items from the perspective of a member of a large online community.

And how about the practical implications?

After so many studies and empirical evidence, can we help a community manager in this situation?
I've got a product support community (X active members, Y post per day) with a SOC-score of 2.4. Is that good? Can I improve that score, given the performance of other communities in this domain? The lowest sub-score is for shared emotional connection with 1.2. Should I invest more time in improving it or is this score generally low for communities like mine?
No, unfortunately, we can't (yet).

Obviously, every approach to measure SO(V)C seems to be different - like the communities to which the measures are applied. The biggest difference is the one between face-to-face communities and online communities. Online communities, for example, use different means of communication, provide a media-rich and playful environment, and they are often anonymous. These differences raise doubt whether SOC measures for face-to-face communities can be applied to communities in a virtual setting [10].

One could use for instance the SCI-2 as it is but it must be clear that what it measures is not the "true" SOVC of the community but only something somehow related to the original SOC-concept. (Of course, remeasuring the same community with the same index from time to time may give one valuable insights into the communities evolution). But the results of community A cannot be compared with those of community B because the SCI-2 may have measured two different SOC-related concepts. Therefore, benchmarking one's community in this way is impossible.
But how about the adapted indices? Does taking one of those questionnaires and applying it to a community give one the community's "true" SOVC? The adapted versions omit several items which were irrelevant in the communities under study but which might be relevant in the community at hand. Much seems to depend therefore on the characteristics of the online community.

So, what can be done?

There is a proven SOC-concept. There are a lot of hints about how to apply it to online communities and there are items that seem to be appropriate to measure the SOVC (somehow). Suppose then, there is an index with applicable items. In a first step, one could use this same index in as many communities as possible to identify those items which measure the SOC best and form the four sub scales - controlling for such community characteristics as size, type (newsgroup, blog, support forum etc.), anonymity, members (gamers, business professionals, consumers etc.), demographics, participation level etc. At this stage, it is perhaps possible to filter out irrelevant items and variables. With many participating communities one could establish a definite set of items and variables to be controlled. The result would be a database for benchmarking purposes. Insert your community's characteristics and the database would provide you with the data from comparable communities.

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[1] McMillan, D., & Chavis, D. (1986). Sense of community: A definition and theory. Journal of Community Psychology, 14, 6-23. Google Scholar. See also Dr. David McMillan's website for a detailed description of SOC and the dynamics of its components and an instructive (and very entertaining) video from the CMX SUMMIT 2014.

[1a] Obst, P., Zinkiewicz, L., & Smith, S. G. (2002). Sense of community in science fiction fandom, Part 1: Understanding sense of community in an international community of interest. Journal of Community Psychology, 30(1), 87-103. Google Scholar.

Obst, P., Zinkiewicz, L., & Smith, S. G. (2002). Sense of community in science fiction fandom, Part 2: Comparing neighborhood and interest group sense of community. Journal of Community Psychology, 30(1), 105-117. Google Scholar.

Obst, P., Smith, S. G., & Zinkiewicz, L. (2002). An exploration of sense of community, Part 3: Dimensions and predictors of psychological sense of community in geographical communities. Journal of Community Psychology, 30(1), 119-133. Google Scholar.

[2] Long, D. A., & Perkins, D. (2003)."Confirmatory factor analysis of the sense of community index and development of a brief SCI." Journal of Community Psychology 31.3 (2003): 279-296. Google Scholar.

[3] Perkins, D. D., Florin, P., Rich, R. C., Wandersman, A., & Chavis, D. M. (1990). Participation and the social and physical environment of residential blocks: Crime and community context. American Journal of Community Psychology, 18(1), 83-115. Google Scholar.

[4] Obst, P., Smith, S. G., & Zinkiewicz, L. (2002). An exploration of sense of community, Part 3: Dimensions and predictors of psychological sense of community in geographical communities. Journal of Community Psychology, 30(1), 119-133. Google Scholar.

[5] Chipuer, H. & Pretty, G. (1999). A review of the sense of community index: current uses, factor structure, reliability, and further development. Journal of Community Psychology, 27, 643-658. Google Scholar.

[6] Obst, P. L., & White, K.M. (2004). Revisiting the sense of community Index: A confirmatory factor analysis. Journal of Community Psychology, 32(6), 691-705. Google Scholar.

[7] Blanchard, A. L. (2007). Developing a sense of virtual community measure. CyberPsychology & Behavior, 10(6), 827-830. Google Scholar.

[8] Blanchard, Anita L. and Markus, M. Lynne (2004). The Experienced "Sense" of a Virtual Community: Characteristics and Processes. Database for Advances in Information Systems; Winter 2004; ABI/INFORM Global p. 65; Google Scholar.

Koh, J., Kim, Y. G., & Kim, Y. G. (2003). Sense of virtual community: A conceptual framework and empirical validation. International Journal of Electronic Commerce, 8(2), 75-94. Google Scholar.

[9] Chavis, D.M., Lee, K.S., & Acosta J.D. (2008). The Sense of Community (SCI) Revised: The Reliability and Validity of the SCI-2. Paper presented at the 2nd International Community Psychology Conference, Lisboa, Portugal. Google.

There is a SCI-2 questionnaire in the section Resources of Community Geek.
For further translations of the SCI-2 into French, Spanish and Portuguese as well as for further resources see: http://www.senseofcommunity.com/show-files.php?category=11

[10] Abfalter, D., Zaglia, M. E., & Mueller, J. (2012). Sense of virtual community: A follow up on its measurement. Computers in Human Behavior, 28(2), 400-404. Google Scholar.

Dienstag, 19. August 2014

Sense of Community: An Alternative Approach

The empirical study of Koh & Kim (2003) [1] on the sense of community is interesting in three respects: Firstly, the authors offer an alternative conceptualization, secondly, they try to identify antecedents, and thirdly, this study reveals the importance of offline activities for the SOC in virtual communtities.

An alternative conceptualisation

Originally, McMillan & Chavis (1968) [2] developed a concept for the sense of community with four elements (cf. Sense of Community in Virtual Communities):
  • Membership: The feeling of belonging to a community.
  • Influence: The feeling that one can make a difference in the community.
  • Integration and fulfillment of needs: The perception that the community's resources will meet ones needs.
  • Shared emotional connection: Members share history, time, places, and experiences.
Koh & Kim (2003) integrate only membership and influence in their concept and add one new dimension - immersion. Integration and fulfillment of needs is omitted because it seems to be more of an antecedent than an element, and shared emotional connection is rather a part of the membership dimension than a independent element. The new aspect immersion is based on the flow concept of Csikszentimihalyi (1975) [3].
"Since virtual community members tend to display immersive (or addictive) behavior toward their community via daily on-line communications the concept of flow is also relevant in the virtual community context."

Possible antecedents of sense of community

By qualitative research (among others a series of in-depth interviews with a group of virtual community leaders) three meaningful antecedents were identified:

1. Leaders' enthusiasm: Community leaders are people who manage (both commercial and non-commercial) virtual communities. They may be either community managers or core members that play a very active role in managing the community. Their engagement during the different stages of the community helps virtual community members feel greater membership toward their community.

2. Offline meetings make up for the comparably low social presence in computer-mediated environments. Offline activities help members understand, trust, and identify other members more easily and they enhance the solidarity and cohesiveness of a virtual community and lead its members to higher levels of membership, influence, and immersion.

3. Enjoyability refers to such outcomes as emotion, pleasure, and satisfaction result from the playfulness experience derived from the community's content and interactions with other members.

Community origin (virtual vs. face-to-face) was introduced as a moderating variable which influences the relationship between the antecedents and the sense of virtual community. The moderator variable weakens or strengthens the effect that the independent variable (antecedent) has on the dependent variable (SOC).

From a list of 50 virtual communities willing to participate in the study, six were dropped because they did not satisfy the selection criteria (i.e., less than 20 members, no interactions for at least two months). Each of the 44 community leaders got five paper-based (not electronic) questionnaires which they randomly distributed to five other community members (n = 220).

On this basis a factor analysis was conducted in order to make sure that each item measured the right antecedent. The effects of the antecedents on the sense of virtual community were examined with three regression analyses.

Results, conclusions and limitations

The sense of virtual community construct was confirmed to have three valid dimensions: membership, influence, and immersion. The dimensions were influenced by the antecedents in the following way:
  • Membership was significantly affected by offline activities, leaders' enthusiasm, and enjoyability - in that order.
  • Influence was significantly affected by offline activities.
  • Immersion was influenced only by enjoyability,
Contrary to expectations, offline activities did not seem to have a significant effect on immersion (members' online activities). The author explain this result with the fact that offline activities is a double-edged sword: Offline activities encourage members to participate actively in the community but due to the loss of anonymity and heightened social presence, offline activities hinder members from becoming fully immersed in the virtual community.

The relationship between antecedents and the dimensions of the sense of community was stronger  for online originated virtual community members than for offline originated virtual community members. Or in other words: Members from online originated virtual communities displayed a much steeper rise in membership and influence values than those from offline originated virtual communities as the values of the two antecedents (i.e., leaders' enthusiasm and off-line activities) increased.

An unexpected and major finding of this study is certainly the important role of offline activities. This is a great opportunity for community management.

Another interesting finding is the significant effect of enjoyability on membership and immersion. Enjoyability represents the pleasure the individual member gets from the virtual community's content and interactions with other members, perhaps a reflection of the needs-fulfillment dimension of the original SOC-concept.

Community management, to be sure, had an impact on membership, but not on influence or immersion. This limited influence is a little bit disappointing.

The authors admit that the study's general applicability may be limited. Although the research model was interpreted mostly in one direction (from antecedent to sense of virtual community), an opposite-direction interpretation is not strictly ruled out. Furthermore, the research model may not be relevant for business-to-consumer communities with few offline activities and few interactions among members.

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[1] Koh, J., Kim, Y. G., & Kim, Y. G. (2003). Sense of virtual community: A conceptual framework and empirical validation. International Journal of Electronic Commerce, 8(2), 75-94. Google Scholar.

[2] McMillan, D., & Chavis, D. (1986). Sense of community: A definition and theory. Journal of Community Psychology, 14, 6-23. Google Scholar. See also Dr. David McMillan's website for a detailed description of SOC and the dynamics of its components and an instructive (and very entertaining) video from the CMX SUMMIT 2014.

[3] Csikszentmihalyi, M. (1975). Beyond Boredom and Anxiety. San Francisco: Jossey-Bass

Dienstag, 22. Juli 2014

Social Relationships in Massive Multiplayer Online Games

Two studies offer very interesting insights into the social networking behavior of players of fantasy massive multiplayer online role playing games (MMORPG or MMOG). In a longitudinal analysis Shen et al. [1] analyzed the driving factors of social relationships in EverQuest II and Ang et al. [2] had a closer look at the players in a guild in World of Warcraft. At second glance, many results can be generalized to communities of practice.

Massive multiplayer online role playing games 

Within a MMORPG each player creates a character to interact with the fictional world and with other players. The players explore the fantasy world, complete quests, kill monsters and gain treasures as well as experience either as solo-players or in player-created (spontaneous) groups or (stable) guilds. The game also has a 'tradeskill' system that allows players to create items for in-game use.

In the creation of a character, the player may choose the character's race and class. Various classes have specialized abilities that are complementary to the skills of other classes. This is a strong incentive to play in groups when the quest turns out to be very difficult.

MMORPGs enable social interaction with other players through grouping and through the creation of guilds. Like players, guilds can gain experience and levels, partially from players completing special tasks, but primarily from guild-oriented quests and tasks. Higher guild levels give access to special rewards unavailable to players who are not in guilds. [3]

Networking in a MMORPG

As theoretical point of reference, Shen et al. chose Campbell's evolutionary framework [4] which explains change in human social systems in terms of an evolutionary selection process: Against the background of scarce resources, not every (randomly originating) variation (= mutation) could be accommodated by the environment, so that only those variations are selected that fit best. These selections are then preserved (retention), duplicated and diffuse into the social system. An extension of this approach to communication networks is described in Monge et al. [5]. In their framework, nodes represent organizations or populations of organizations in a community, and ties can be considered as mechanisms of resource exchange among these nodes. Following the evolutionary argument, an organizational community is constrained in its capacity to sustain the nodes as well as the ties. Monge et al. label them as:
  • member carrying capacity, which defines the upper limit of nodes the community can support, and
  • relational carrying capacity, which defines the upper limit of ties the community can support. 
Applying this concept, Shen et al. investigate the ties (relationships) between individual gamers (nodes) which differ for instance in age, gender, level etc. In this case the scarce resource is the (limited) capacity to initiate and maintain ties with other players (limited relational carrying capacity). This reflects the concept of Dunbar's number, a suggested cognitive limit to the number of people with whom one can maintain stable social relationship with a commonly used value of 150. [6] Thus variation can be considered as the numerous possibilities of tie formation among all the available nodes in  the network, and all possible ties are also selected based on their fitness, which is „the propensity of a relationship to sustain itself".

And this is how a player's network evolves:
  • In the beginning many relationships originate from random chance, but later the networking behavior becomes more selective (identifying compatible players) and the player is also better at maintaining these contacts. Therefore, the size of a player’s social network will shrink as the player advances in the game and gains more experience. 
  • The longer a tie is maintained between two players, the less likely a disruption is. This reflects the fact that organizational structures tend to develop an internal inertia as long as they provide mutual benefits for those involved.
  • Given the built-in advantage for groups with players with complementary skills, one would expect that ties between players with the same skills are more prone to decay than ties between players with complementary skills. However, this hypothesis did not receive empirical support in the study
  • Whether a quest is feasible, depends on the experience (level) of the player. Playing in a group, a clearly less experienced player has not much to contribute to the group’s success. Therefore, when level difference increases, tie decay increases as well. Furthermore, EverQuestII discourages teams of players with a great level difference because the high-level player gets most of the experience points.
  • Players who are members in a guild are much more likely to maintain the ties with other guild members.
Interestingly, being of the same gender or having the same age has no significant influence on tie decay. Being located in the same geographic area (measured by whether two players are from the same state) attenuates tie decay. This, of course, may be due to preexisting familiar or friendship networks. One would also expect that ties among players who spend a lot of time in the game are  less likely to decay because these players are experienced and have routines for engaging in and keeping relationships. But this conclusion was not confirmed.

The guild - a community of practice

Ang et al. [2] analyzed the social roles and interactions of guild members. A content analysis of the messages during a representative period revealed the following seven topic categories:
  • group management: soliciting/responding to invitations, identifying group members, deciding meeting points, (re)structuring the group and leaving the group;
  • task coordination: pointing out targets, coordinating actions, looting, discussing strategies and trading;
  • ask for help: in situations that need immediate solutions such as the solution of quests, equipments, asking for game items and money;
  • give help/answer questions;
  • friendly remarks: apologizing, greeting, laughing, saying thank you, typing smileys for nonverbal communication (waving, making a bow etc.);
  • small talk not directed towards achieving game goal or completing game task (telling jokes, being sensitive to others, being supportive and being encouraging);
  • real life chats: chats that reveal the member's real life identities (real life gender, nationality, etc.) and chats about real life topics such as work/college life.
Using a special algorithm (CONCOR), the guild members were clustered in three blocks. The players were placed in the same block if they had similar ties to other players:

Ang, C. S., & Zaphiris, P. (2010). Social Roles of Players in MMORPG Guilds: A Social Network Analytic Perspective. Information, Communication & Society, 13(4), 592-614.
  • Core members: They are densely inter-connected and moderately connected to other blocks. They are very likely to be players who have been longer in the guild and know each other well. They are actively involved in game chat, group management and give help, but not ask for help. Some core players excell primarily with their knowledge (knowledge players) others in socializing (social players). 
    • Knowledge players, by giving help, are the guild's resource which attracts other players into the guild. 
    • Social players provide a friendly atmosphere and maintain the guild's cohesiveness (= more connections, closer and denser ties).
  • Semi-periphery members: This block consists of loosely interconnected players who try to get involved in the guild community. They seek help and give help, and show active involvement by participating in game chat and group management.
  • Periphery players: These players are disconnected. Their main goal is to get help from the guild but not to get involved in the guild community. They have access to a lot of other players, thus increasing the chance of getting help. There are two types: newbie and freeloaders. 
    • Newbies are new to the game in general (low levels, needing help on basic issues). It seems that the career progression of a newbie first leads to the semi-periphery with a subsequent change of behavior and then to the core group. 
    • Freeloaders (usually higher levels, typically asking quest-related questions) are using the guild only as an instrumental tool for their task interaction. 
Ang, C. S., & Zaphiris, P. (2010). Social Roles of Players in MMORPG Guilds: A Social Network Analytic Perspective. Information, Communication & Society, 13(4), 592-614.

Although the core members interacted with members from all three blocks, they interacted largely within the block. They were particularly strongly connected internally in game chat and group management categories and least internally connected in give help category.

Semi-periphery members interacted both within the block and with core members. They were more strongly connected to core members than to members from the same group. Although in general their interaction was external to the group, they tended to interact with core members the most through ‘ask for help’ and ‘give help’ categories. Their interaction was, however, the least external when it comes to ‘game chat’ activity, implying that their internal interactions revolved mainly around ‘game chat’.

Interestingly, periphery members only interacted with core members.
Ang, C. S., & Zaphiris, P. (2010). Social Roles of Players in MMORPG Guilds: A Social Network Analytic Perspective. Information, Communication & Society, 13(4), 592-614.

What are the major takeaways?

The popular prejudice („Online-relationships are random and short-lived and qualitatively inferior to real-life relationships.“) is wrong. Online too, people want to engage in stable and reliable relationships that match their needs for company, support, information and recreation. But low entry- and exit-costs mainly due to the possibility to remain anonymous make it possible „to try out“ more people than in real life.

Community of practice: Although this may sound somewhat far-fetched, anything that requires special expertise qualifies as a domain for a community of practice. And in fact, running a guild needs a lot of experience. And so I wonder, whether the three groups (core, semi-periphery and periphery) and the interaction pattern, can be generalized to other communities of practice.

Personal bonds among members (virtual or real) are essential for a lively, self-sustained community. And much depends on the members of the core group. Their expertise and their receptiveness for the needs of other members are crucial for the accumulation of social capital.

Gamification/Lurking: There is an ongoing debate whether adding game features (rank lists, badges etc.) as an incentive for lurkers is either beneficial, detrimental (people will expect another reward for their contribution next time) or irrelevant. The example of the guild indicates that some players chose to associate themselves more closely to the community and some players chose to stay in the periphery. In other words, it doesn't seem to be a motivational problem. But qualifiers like ranks or badges can be useful if they convey an information about the "level" of the member like her or his expertise or the number of answered questions.

Socializing newbies: New members face two problems: They must learn the rules of the game (= community) - mostly from observing the behavior of other members - and they must start to build their personal network. I'd bet that the more help they get from other members at this stage the more newbies will go to the semi-periphery. And once again, the burden lies on the members of the core group as the interaction patterns show.

Age, gender, time spent in the community don't influence tie quality. This is (somewhat) obvious for age and gender because normally you don't know whether the other player is a man or a woman and how old she/he is. But the irrelevance of the time spent in the game is counter-intuitive. It seems that much depends on the quality of interaction instead.

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[1] Shen, C., Monge, P., Williams, D. (2014). The evolution of social ties online: A longitudinal study in a massive multiplayer online game. Journal of the association for information science and technology. Published online in Wiley Online Library. DOI: 10.1002/asi.23129

[2] Ang, C. S., & Zaphiris, P. (2010). Social Roles of Players in MMORPG Guilds: A Social Network Analytic Perspective. Information, Communication & Society, 13(4), 592-614. Google Scholar

[3] EverQuest II (n.d.). Retrieved May 30, 2014 from http://en.wikipedia.org/wiki/EverQuest_II

[4] Campbell, D. T. (1965). Variation and selective retention in socio-cultural evolution. In H. R. Barringer, G. I. Blanksten & R. W. Mack (Eds.), Social change in developing areas: A reinterpretation of evolutionary theory (pp. 19-48). Cambridge, MA: Schenkman.

[5] Monge, P., Heiss, B. M., & Margolin, D. B. (2008). Communication Network Evolution in Organizational Communities. Communication Theory, 18(4), 449-477. Google Scholar.

[6] Dunbar's number (n.d.). Retrieved May 30, 2014 from http://en.wikipedia.org/wiki/Dunbar's_number

[7] Frost, J., Vermeulen, I. E., & Beekers, N. (2014). Anonymity Versus Privacy: Selective Information Sharing in Online Cancer Communities. Journal of medical Internet research, 16(5), e126. Google Scholar.

Freitag, 30. Mai 2014

Communities of Action: Are Online Activists Different from Offline Activists?

Theoretically, the question whether political online participation differs from offline participation can be answered in two ways [1]:
  • The mobilization thesis argues that due to new information and communication technologies, previously not engaged groups can be reached. Therefore, online activists should be different from offline activists.
  • The reinforcement thesis assumes that the Internet won't change existing patterns of political participation. It might even widen the participatory gaps between advantaged and disadvantaged populations. Or in other words: On- and offline activists should be more or less the same bunch of people.
Oser et al. [2] tried to settle the question analyzing the Pew Internet and American Life Project’s August 2008 survey (Pew Internet and American Life Project 2008). The survey was based on telephone interviews among adults (n = 2.251, age: 18+) who were asked questions regarding online and offline participation. The survey took place during the presidential campaign of 2008 (Obama vs. McCain) which hints to possible limitations of the survey as the Obama campaign was particularly successful at mobilizing traditionally less engaged populations such as young people and women.

The authors used latent class analysis (LCA) and - based on the results - examined the characteristics (age, gender socio-economic status) of the identified participation types. In a latent class model people can be categorized  into different types (latent classes) based on their observable behavior. Participation indicators used in the analysis were:
  • signing a petition (offline, online)
  • donating money (offline, online)
  • contacting a government official in person, by phone, or by letter (offline) or by email (online)
  • starting/joining a political group or group supporting a cause on a social networking site (online)
  • being an active member of a group that tries to influence policy, except a political party (offline)
  • attending a political rally, speech, or organized protest (offline)
  • working/volunteering for a political party or candidate (offline)
The LCA identified four distinct groups: the disengaged (73 % of all respondents), the contacters (10 %), the offline activists (9 %), and the online activists (8 %). All four groups have a different participation repertoire.

Oser, J., Hooghe, M., & Marien, S. (2013). Is online participation distinct from offline participation? A latent class analysis of participation types and their stratification. Political Research Quarterly, 66 (1), 91-101.

Example: The online activist's probability of online donating  is 51.3 % in comparison to 5.6 % in the sample population.

Online participation is a distinct type of participation
The findings provided strong evidence in support of the mobilization thesis. Online activists are a distinct group in comparison to the three other identified participation types. Although online activists prefer online forms of participation, they are also involved in offline participation.

Mixed results for the influence of age, gender and socio-economic status
Mobilization thesis is strongly confirmed regarding age, and it is also confirmed for gender. For socio-economic status, however, the findings suggest a reinforcement of traditional education and income inequalities in online political participation.
  • Age: Young people tend to engage with politics in a new way through online means.
  • Gender: There is no evidence for a gender divide for any of the participation types. Women seem to catch up with mens' early adoption of new technologies, especially regarding the use of social media (note the inclusion of political social media use in the survey).
  • Socio-economic status: The socio-economic stratification is basically the same for the online as for the offline activist type. The advantaged are more active in both online and offline participation, suggesting a reinforcement of traditional education and income inequalities in online political participation and limiting the democratic potential of the Internet for impacting upon patterns of political participation and participatory inequality.
Targeting potential activists for communities of action
A community of action is a group of people brought together by their desire to change something. Often these communities are initiated by non-profit or fundraising organizations. [3] The study of Oser et al. gives certain hints how to optimize the activities:
  • Online activists don't tend to donate offline. So offer them a possibility to donate online.
  • Contacters are relatively inactive in a number of participation acts (e.g., party work, donating offline, demonstrating) or essentially on par with the general population (e.g., active member of an offline and online political or social group and online donating). Therefore, efforts to stimulate other types of engagement in contacters may be futile.
  • Offer possibilities for online participation in order to reach out to younger people and use social media networks in order to reach out to women.
  • The chance of making a difference is higher, when the cause is suited for the mobilization of the advantaged.
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[1] Norris, P. (2000). A Virtuous Circle: Political Communications in Postindustrial Societies. Cambridge, UK: Cambridge University Press. Chapter 12.

[2] Oser, J., Hooghe, M., & Marien, S. (2013). Is online participation distinct from offline participation? A latent class analysis of participation types and their stratification. Political Research Quarterly, 66 (1), 91-101. Google Scholar

[3] Millington, R. (2014). Types of community and actives within the community. Retrieved May 28, 2014, from http://www.feverbee.com/2012/10/types-of-community-and-activity-within-the-community.html


Dienstag, 6. Mai 2014

Sense of Community: Is there a fifth dimensions?

In three papers, Obst et al. [1, 2, 3] published the results of their investigation about the sense of community (SOC). They had asked 359 members of SF fandom attending Aussiecon 3, the 1999 World Science Fiction Convention about the way they feel about the fandom community (a - relational - community of interest with membership from all over the world) and about their neighbourhood (a geographical community). The main research interest was to find out whether McMillan and Chavis' four dimensions of SOC played a role in both community types (relational and geographic) and whether there is a separate fifth factor - conscious ingroup identification. Both assumptions were confirmed by the results.

What is sense of community?
McMillan and Chavis (1986) [4] suggest four dimensions which work together dynamically in order to create and maintain an overall sense of community :
  • Membership: The concept includes emotional safety derived from membership, the sense of belonging and identification with the community, personal investment in the community, leading to stronger bonds, and some kind of common symbol system, which unites a community. These attributes go together in a mutually self-reinforcing way.
  • Influence means a reciprocal relationship between individuals and the community in terms of their impact on one another. Influence is a bi-directional concept, as for a group to be attractive, an individual must feel they have some control and influence over it, while, on the other hand, for a group to be cohesive it must also influence its individual members. McMillan and Chavis (1986) state that pressure of conformity from community members actually comes from the needs of individual members for consensual validation. In turn conformity serves as a force for cohesiveness.
  • Integration and Fulfillment of Needs: Members must perceive the association to the community as rewarding for the individual members (like status of membership, success of the community, and the perceived competence of other members).
  • Shared Emotional Connection: The more people interact, the more likely they are to form close relationships. The more positive this interaction, the stronger the bond developed. 
In 1996 McMillan [5] revisited the theory:
  • Membership was reinterpreted as Spirit, emphasizing friendship and belonging over boundaries.
  • Influence was replaced with Trust, emphasizing the development of community norms leading to order, and the equal distribution of power leading to authority based on principle and clear decision making capacity, all of which allow spirit to grow and flourish.
  • Fulfillment of Needs was replaced with Trade, acknowledging the myriad kinds of rewards individuals gain from belonging to communities. The importance of similarity between members was also highlighted as an important bonding force previously neglected in this dimension.
  • Shared Emotional Connection, was replaced with Art, or collective memories, which McMillan described as stories of shared dramatic moments in which the community shares in common experiences representing the community’s values and traditions. However, the primacy of contact and of quality interaction to emotional connection is again highlighted in McMillan’s reinterpretation.
These dimensions work together to create an overall SOC. Art supports Spirit, Spirit with respected authority becomes Trust, Trust forms the basis of social Trade, and together these elements create a shared history symbolized by Art. In this way, McMillan’s four elements of SOC are linked together in a reinforcing circle.

And the results of Obst et al.?
  • McMillan and Chavis' four dimensions of SOC could be estabished in both communities (SF fandom and neighbourhood).
  • In-group identification was a separate 5th dimension in both community types. These results suggest that separate aspects of identification may relate to different dimensions of SOC. While identification’s more affective components and connection with other members are subsumed within McMillan and Chavis’ theorized dimensions of PSOC, knowledge and awareness of group membership is a separate and important dimension, not included within the SCI.
  • Furthermore, participants reported higher levels of global SOC with fandom than with their geographical communities, a pattern that also emerged across all factors separately. This may be due to the fact that members choose to belong to such communities and are drawn together through a common interest. In the present study this finding is of particular significance, as SF fandom operates on an international basis with fewer geographical connections than in many other relational communities. However, this study is limited in making stronger conclusions in relation to this finding, as participants were in a fannish context (a SF convention) rather than in their local neighborhood. Replication of this research is needed with data collected in a more neutral context.
  • All five dimensions were significant predictors of overall sense of community in both community types.
    • Conscious identification with fandom emerged as the strongest predictor, while in the neighborhood setting it was the weakest predictor. 
    • Belonging was a strong predictor in both communities. This suggests that belonging is an important dimension of sense of community in whatever context we are examining. 
    • Identification, however, seems to be more important in the communities to which we choose to belong than in those communities which we may have made a less conscious decision to join. 
    • Influence was an important predictor in geographical communities, however not at all important in the interest community. This may again be due to the element of perceived choice. If you choose to belong to an association due to common interest the need for influence over that association may be less than the need to feel some control or influence over the area in which you live.
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[1] Obst, P., Zinkiewicz, L., & Smith, S. G. (2002). Sense of community in science fiction fandom, Part 1: Understanding sense of community in an international community of interest. Journal of Community Psychology, 30(1), 87-103. Google Scholar.

[2] Obst, P., Zinkiewicz, L., & Smith, S. G. (2002). Sense of community in science fiction fandom, Part 2: Comparing neighborhood and interest group sense of community. Journal of Community Psychology, 30(1), 105-117. Google Scholar.

[3] Obst, P., Smith, S. G., & Zinkiewicz, L. (2002). An exploration of sense of community, Part 3: Dimensions and predictors of psychological sense of community in geographical communities. Journal of Community Psychology, 30(1), 119-133. Google Scholar.

Obst, P. (2004) Community Connections: Psychological sense of community and identifcation in geographical and relational settings. Thesis. Retrieved March 14, 2014 from http://eprints.qut.edu.au/15971/1/Patricia_Obst_Thesis.pdf

[4] McMillan, D., & Chavis, D. (1986). Sense of community: A definition and theory. Journal of Community Psychology, 14, 6-23. Google Scholar.

[5] McMillan, D. (1996). Sense of community. Journal of Community Psychology, 24, 315-325. Google Scholar.



Donnerstag, 1. Mai 2014

Community feedback is likely to perpetuate undesired member behavior

The feedback of other community members is considered to be an important corrective factor in moderating community discussions. Liking a post, voting on a comment, rating are the most common feedback mechanisms. Theoretically, feedback would lead users to behave in ways that benefit the community. But investigating four online sites,
  • CNN.com (general news),
  • Breitbart.com (political news),
  • IGN.com (computer gaming), and 
  • Allkpop.com (Korean entertainment
Cheng et al. [1] found some quite counter-intuitive results.

One commonality of these sites is that users post comments on (news) articles, where each comment can then be up- or down-voted by other users.

From a behaviourist point of view (here: operant conditioning), positive ratings should act as a “reward” and negative ratings as a“punishment”. So one would predict that feedback encourages users to generate better content in the future, and that users with negatively evaluated content will contribute less than rewarded users.

The impact on posting behavior
  • Negative feedback: Authors of negatively-evaluated content contribute more, their future posts are of also lower quality, and perceived by the community as even worse. Further, these authors are more likely to subsequently evaluate their fellow users negatively, percolating these effects through the community. 
  • Positive feedback neither encourages rewarded authors to write more, nor does it improve the quality of their posts. 
  • Users that receive no feedback are most likely to leave a community. 
Interestingly, evaluations polarize the community the most when positive and negative votes are equally split.

The impact on voting behavior

User behavior is largely tit-for-tat: Users with predominantly negative/positive evaluations will negatively/positively evaluate others. But very negatively evaluated people actually respond in a positive direction: The proportion of up-votes they give is higher than the proportion of up-votes they receive. And users receiving many up-votes appear to be more “critical”, as they evaluate others more negatively.

What are we to make of these findings?

The authers conclude that community feedback does not automatically drive behaviour in a direction that is beneficial to the community. Instead, it is likely to perpetuate detrimental behaviour. This, of course, raises the question whether the content evaluation mechanisms currently implemented in social media systems have effects contrary to the interest of the community.

Of course one could blame the theory: Despite of being a fundamental framework in behavioral psychology, there seems to be only limited empirical evidence that operant conditioning has noteworthy effects on human beeings. [2]

But did Cheng et al. investigate communities after all? Probably not. In a very general sense, the term community designates people gathering on a virtual site, even though the term audience would be  more appropriate. In a strict sense, a community comes into existence when users develop a significant sense of (virtual) community (SOVC). According McMillan and Chavis [2], sense of community consists has four components:
  • membership (feelings of emotional safety with a sense of belonging and identification),
  • influence (exertion of one's influence on the community with reciprocal influence of the community on oneself),
  • integration and fulfillment of needs (beeing supported and giving support, thereby reinforcing one to behave in a manner acceptable to the community),
  • shared emotional connection (positive affect related to community membership, shared history).
So I would expect, that members with a high SOVC but negatively rated contributions are likely to try to do better next time. Members with a low SOVC, on the other hand, may behave like described by the authors in their study or they may leave the community.
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[1] Cheng, J., Danescu-Niculescu-Mizil, C., & Leskovec, J. (2014). How Community Feedback Shapes User Behavior. Retrieved May 1, 2014, from http://www-cs.stanford.edu/people/jure/pubs/disqus-icwsm14.pdf

[2] Baron, A., Perone, M., & Galizio, M. (1991). Analyzing the reinforcement process at the human level: Can application and behavioristic interpretation replace laboratory research?. The Behavior Analyst, 14(2), 95. Google Scholar.

[3] McMillan, David W. and Chavis David M. (1986). Sense of Community: A Definition and Theory.Journal of Community Psychology Volume 14, 6-23. Google Scholar.

For further information about the SO(V)C concept and possible ways to measure it, see the post: "Sense of community in virtual communities" (12.8.2013)

Montag, 28. April 2014

Successfull Managment of Online Health Communities

Browsing the Internet, I stumbled across these three interesting articles about the successful management of online health communities. Here are the (slightly modified) abstracts:

Community management that works: How to build and sustain a thriving online health community 

Colleen Young [1] (see her health care social media blog) describes the community management strategies as well as the resources, the challanges and the expertise needed to build and maintain a thriving online health community. Her paper draws on insights from an ongoing study and observation of online communities as well as experience managing and consulting a variety of online health communities. Discussion includes effective community building practices relevant to each developmental stage of the community, such as outreach and relationship building, data collection, content creation, and other techniques that ensure the survival and steady growth of an online health community.

Enabling community through social media

Anatoliy Gruzd and Caroline Haythornthwaite  [2] demonstrate how social network analysis provides a vocabulary and set of techniques for examining interaction patterns via social media. Using the case of the #hcsmca online discussion forum (hscmca stands for Health Care Social Media Canada), this paper highlights what has been and can be gained by approaching online community from a social network perspective, as well as providing an inside look at the structure of the #hcsmca community. Social network analysis was used to examine structures in a 1-month sample of Twitter messages with the hashtag #hcsmca (3871 tweets, 486 unique posters). Network connections were considered present if the individual was mentioned, replied to, or had a post retweeted.

Network analyses revealed patterns of interaction that characterized the community as comprising one component, with a set of core participants prominent in the network due to their connections with others. Analysis showed the social media health content providers were the most influential group based on in-degree centrality. However, there was no preferential attachment among people in the same professional group, indicating that the formation of connections among community members was not constrained by professional status.

Growing a professional network to over 3000 members in less than four years

Noreen Frisch et al. [3] analyzed “InspireNet”, a virtual professional network for health professionals permitting documentation of when and how professionals take up Web 2.0 and social media. Overall evaluation methods included tracking website use, conducting two member surveys, and soliciting member feedback through focus groups and interviews with those who participated in electronic communities of practice (eCoPs) and other stakeholders.

Network growth exceeded all expectations. Members engaged with varying aspects of the network’s virtual technologies, such as teams of professionals sharing a common interest, research teams conducting their work, and instructional webinars open to network members. Members used wikis, blogs, and discussion groups to support professional work, as well as a members’ database with contact information and areas of interest. Nonetheless, creation of a Web 2.0 and social media platform is not sufficient, in and of itself, to attract or sustain a vibrant community of professionals interested in improving their practice. Essential support includes instruction in the use of Web-based activities and time management, a biweekly e-Newsletter, regular communication from leaders, and an annual face-to-face conference.
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[1] Young, C. (2013). Community management that works: How to build and sustain a thriving online health community. Journal of medical Internet research, 15(6). Google Scholar

[2] Gruzd, A., & Haythornthwaite, C. (2013). Enabling Community Through Social Media. Journal of medical Internet research, 15(10). Google Scholar.

[3] Frisch, N., Atherton, P., Borycki, E., Mickelson, G., Cordeiro, J., Lauscher, H. N., & Black, A. (2014). Growing a Professional Network to Over 3000 Members in Less Than 4 Years: Evaluation of InspireNet, British Columbia’s Virtual Nursing Health Services Research Network. Journal of medical Internet research, 16(2). Google Scholar.