Difference between revisions of "Understanding user information sharing behaviors"
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== Goal == | == Goal == | ||
| − | Identifying the relationship between likelihood that a user retweets a tweet with some other network and linguistic factors, e.g., the relative position of the follower and the followee in the network (they are in the same political community or not), or the topic of the tweets, etc. | + | Identifying the relationship between likelihood that a user retweets a tweet with some other network and linguistic factors, e.g., the relative position of the follower and the followee in the network (they are in the same political community or not), their centralities within the network and their communities, or the topic of the tweets, etc. |
== Methods == | == Methods == | ||
Revision as of 14:52, 8 October 2012
This is an assignment project for Social Media Analysis course in Fall 2012
Project Proposal
Characterizing user behaviors in retweeting in Twitter
Team Members
Goal
Identifying the relationship between likelihood that a user retweets a tweet with some other network and linguistic factors, e.g., the relative position of the follower and the followee in the network (they are in the same political community or not), their centralities within the network and their communities, or the topic of the tweets, etc.
Methods
- Using bag-of-words based classifiers to identify user community label
- Measuring user relative position in network using their community label and other
Data Set
The dataset is crawled from Twitter using Twitter's APIs. Starting from a set of selected influential users, we expanded the set by including their followers and followees. Tweets, including retweets, from all the users then will be crawled in daily basis.
