Using Social Network Analysis to Study the Interaction Patterns in an Online Knowledge Community

Angela Heath Long Island University, Brookville, New York 11 548. Email: aheathOl @cwpost.liu.edu

Traditional group study methodologies focus on the study of individuals that comprise a group. Social Network Analysis (SNA) focuses on the relationships between members that make up a group. This research demonstrates the use of SNA and content analysis as a mixed methodology for studying interaction patterns of members in a Web-based knowledge community. Since this project is an initial investigation, further questions and directions will be included.

Introduction Traditional study of online groups involves a combination

of content analysis and interview techniques. Social Network Analysis (SNA) is a methodology for group study that examines relationships rather than individual behavior. This research demonstrates the use of SNA and content analysis as a mixed methodology for studying interaction patterns of members in Abuzz.com, a Web-based knowledge community. Specifically, the study investigated - 1) the frequency of participation of the Abuzz members, 2) the existence of a ”core” group of Abuzz members and 3) the communication patterns of members in the ‘‘core“ group and the non -”core” group.

Background Abuzz.com is a free web-based information-sharing

environment started in 1996 by the New York Times Digital, the Internet division of the New York Times Company. Users can give and receive information at Abuzz using asynchronous and hyperlink-based email. Abuzz consists of 16 designated categories with varying subsections in each category.

Upon joining Abuzz, members voluntarily join as many or as few categories as they like. Users receive email notifications when questions are posted to that category. Acting as information givers, users log into their Abuzz accounts, browse through their chosen categories and answer questions. In order to post a question at Abuzz, users must create an account, select categories andor subsections in which to send their questions. Users receive email notifications when their questions are answered.

Data Collection From late March 2001 until mid May 2001, email

transcripts from the 16 main categories at Abuzz were collected. Eight weekly collections of data were made on 2 randomly selected days in the week. The transcripts came from randomly chosen subsections within the 16 categories. Data collection consisted of copying email transcripts of previously posted questions submitted by Abuzz users. In all, 5 12 email transcripts were collected and recorded.

Discussion Frequency of Participation at Abuzz

At Abuzz, participation occurred in a variety of ways. In all, the participation of 409 members was studied. To facilitate a more detailed analysis, members’ participation patterns were categorized into 3 groups. Group A (2%) consisted of members who participated frequently (more than 2 postings) in more than 5 main categories. Group B (8%) consisted of members who participated infrequently (1-2 postings) in 3 to 5 main categories. Group C (90%) consisted of members who participated infrequently (1 posting) in 1 or 2 main categories. Although, there were members of groups B and C who had high interaction rates, this was not considered the same as the members in group A. High interaction rates were not deemed to be equivalent to frequency of participation.

Existence of a Core Group SNA as a methodology involves quantifying and

visualizing observations of the relational ties of group members. Generally there are two types of network analysis - ego network analysis and complete network analysis. Ego network analysis involves identifying and focusing on the relationships with core members (actors) in a network. Complete network analysis involves simply identifying all of the types of relationships and ties that exist in a group dynamic. Ego network analysis is helpful when the group being studied is large or hard to define. (Wellman, 1982)

At Abuzz, members of groups A and B (10% or 41 members) could be considered a “core” group based on their high frequency rates. But, assuming the significance of this proposed “core” group without exploring it within

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the structure and ecology of the Abuzz environment would Communication Patterns of the “core ” vs. non- be erroneous. “core ” groups

In ego network analysis, several dimensions can be A content analysis was conducted on the email postings examined, namely - centrality and support. Centrality involving a sample of 5 members from the “Core” group describes a structural characteristic of the relationships of and the non-‘‘Core” group. Table 2 SUmmarizes common members (actors) in a network. Centrality can also be used ~~mmunications for outgoing email messages involving to measure a member’s importance and prestige in a members of the “core” and the non-“core” groups. network. Freeman (1979), defined in-degree and out- degree as being the # of messages directed at a member and the # of messages initiated by a member, respectively. A member with a high in-degree number is well respected and has prestige and importance within the network. Members with high out-degree numbers tend to be leaders and take a more active role in the network. Using a traditional conversation analysis, it was observed that a sample of members of the proposed “core” group had on average higher in-degree and out-degree numbers than members not

Table 2 . Percentage of material-based vs. emotionally- based content of outgoing messages of “core” group

members vs. non- “core” group members. (n = 5)

based based “core” 36% 64%

Total Material- Ernotionally- fl 77% 23% NMHXNX’’

in the “core”. (see Table 1) Future Directions Table 1. Average In-degree and Out-degree numbers of

Core group members vs. non-core group members.

“core” members

Non-“core” members

It should be noted that there were members of the non- “core” group who had higher in I out degree numbers than their “core” member counterparts. But initial investigations seem to suggest that the higher in-degree and out-degree numbers of the “core” are not just the result of participating more.

Support in social network analysis refers to the type of relationship or “ties” expressed from one member to the other. Typically, members can provide several forms of support to one another. Namely, 1) emotional aid, 2) material aid (money, service, goods), 3) information and 4) companionship. In his Social Resource Theory, Lin (1982) relates the strength of ties between actors to the types of resources that are exchanged. He theorizes that stronger ties are more likely to be formed through exchanging life experiences or giving emotional support. Weaker ties are more likely formed when materially-based information (such as on job hunting, buying products, etc) is exchanged between actors.

At Abuzz, material resource-based ties AND emotionally-based ties were frequently observed for “core” members.

Further investigations of the “core” group could prove very usefbl in studying the participation patterns of members in other communities. Participation is essential to the success of any of these online communities. For instance, do members of the “core” maintain their level of participation over long periods of time? Would similar “core” groups exist for other types of communities? Does the use of different technologies (i.e. email, real-time chat) affect the existence of the “core”?

Social network analysis introduces new approaches to understanding how people participate when online. The study of frequent participators in online environments can be invaluable in the development of new communities.

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Journal of Sociology, 78(6), 1360- 1380. Lin, N. (1 982). “Social Resources and Instrumental Action.“

(pp.131-45) In by Lin, N. and Marsden, P. (eds.) Social Structure and Network Analysis, Beverly Hills,CA: Sage.

Marsden, P. & Campbell, K.E. (1984). Measuring tie strength. Social Forces, 63,482-501.

Wellman, B. (1982). Studying personal communities. In P. Marsden & N. Lin (Eds.), Social structure and network analysis. (pp. 61 -80). Beverly Hill, CA: Sage.

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