decomposing discussion forums using user roles
TRANSCRIPT
Decomposing discussion forums using user roles
Jeffrey Chan & Conor HayesFriday seminar
8/20/2010Presenter: Asta Zelenkauskaite
Feature-based profiling
Users roles are identified by the features (indicators) to profile user behavior
◦Visualization techniques Downside: used only for small-scale studies
◦Proposed solution: soc net analysis Ego-network analysis and the out-degree
distribution
Data
Boards.ie – the largest discussion board in Ireland
596 forums75400 users 244850 threads 4.3 mln posts
Forums
Optimal number of clusters
Analysis
Weighted directed graph Ego-net graph – reply graph (multi-edge
graph)
20 forums from 01/07/2006 – 31/12/2006.
Features
Initially 50 features, redundant eliminatedStructural features (as communication btw
users)◦Unweighted directed graphs◦From interaction with their neighbors
Reciprocity features Persistence features Popularity features Initialization features
Structural features (operationalization)
◦From interaction with their neighbors Reciprocity features
◦% of bi-directional neighbors (represents the % of the neighbors of a user where there is both in and out edges – they have replied to each other).
Persistence features◦The length of the conversations a user typically engages in
(mean and sd of the posts per thread). Popularity features
◦Ratio of a users’ in-neighbors (% of in-degree) # of replies◦% of the posts where there is at least one reply to the user.
Initialization features◦ Initiated % of msgs by a user.
User role discovery approach
Data cleaning◦Filtering out low-degree, low posting users
User grouping◦Via number of neighbors
User roles
Joining conversationalists ◦ the ones who do not initiate but post replies
Taciturns◦ Low reciprocity (rarely get involved into two-way communication)
Elitists◦ Low % of neighbors w/ two-way communication
Supporters◦ Middle range of the statistics of all features
Popular participant◦ Do not initiate many threads but get involved with a large percentage of
users of a forum Grunts
◦ Similar to taciturns, relatively high levels of reciprocity. Ignored
◦ Extremely low % posts being replied to (not very popular)
clusters
Results: Forum composition
Some forums are distinctively different from the others (eg. personal issues)
Difference in grouping by conversationalists vs taciturns
Some topics determine certain composition
Discussion
Is it impossible to assess the ‘success of functioning’ from the composition of the group?