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The number of users on Twitter has drastically increased in the past years. However, Twitter does not have an effective user grouping mechanism. Therefore tweets from other users can quickly overrun and become inconvenient to read. In this paper, we propose methods to help users group the people they follow using their provided seeding users. Two sources of information are used to build sub-systems: textural information captured by the tweets sent by users, and social connections among users. | Interactive Group Suggesting for Twitter Zhonghua Qu Yang Liu The University of Texas at Dallas qzh yangl @hlt.utdallas.edu Abstract The number of users on Twitter has drastically increased in the past years. However Twitter does not have an effective user grouping mechanism. Therefore tweets from other users can quickly overrun and become inconvenient to read. In this paper we propose methods to help users group the people they follow using their provided seeding users. Two sources of information are used to build sub-systems textural information captured by the tweets sent by users and social connections among users. We also propose a measure of fitness to determine which subsystem best represents the seed users and use it for target user ranking. Our experiments show that our proposed framework works well and that adaptively choosing the appropriate sub-system for group suggestion results in increased accuracy. 1 Introduction Twitter is a well-known social network service that allows users to post short 140 character status update which is called Tweet . A twitter user can follow other users to get their latest updates. Twitter currently has 19 million active users. These users follows 80 other users on average. Default Twitter service displays Tweets in the order of their timestamps. It works well when the number of tweets the user receives is not very large. However the flat timeline becomes tedious to read even for average users with less than 80 friends. As Twitter service grows more popular in the past few years 519 users following list starts to consist of Twitter accounts for different purposes. Take an average user Bob for example. Some people he follows are his Colleagues some are Technology Related People and others could be TV show comedians . When Bob wants to read the latest news from his Colleagues because of lacking effective ways to group users he has to scroll through all Tweets from other users. There have been suggestions from many Twitter .
