Name
Abstract | ||
|---|---|---|
Judging topical expertise of micro-blogger is one of the key challenges for information seekers when deciding which information sources to follow. However, it is unclear how useful different types of information are for people to make expertise judgments and to what extent their background knowledge influences their judgments. This study explored differences between experts and novices in inferring expertise of Twitter users. In three conditions, participants rated the level of expertise of users after seeing (1) only the tweets, (2) only the contextual information including short biographical and user list information, and (3) both tweets and contextual information. Results indicated that, in general, contextual information provides more useful information for making expertise judgment of Twitter users than tweets. While the addition of tweets seems to make little difference, or even add nuances to novices' expertise judgment, experts' judgments were improved when both content and contextual information were presented. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2207676.2208410 | CHI |
Keywords | Field | DocType |
twitter user,information source,information seeker,user list information,expertise judgment,useful different type,contextual information,inferring expertise,useful information,topical expertise,recommender system,recommendation system | Recommender system,Seekers,World Wide Web,Contextual information,Computer science,Knowledge management,Human–computer interaction | Conference |
Citations | PageRank | References |
12 | 0.79 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Q. Vera Liao | 1 | 173 | 25.59 |
| Claudia Wagner | 2 | 12 | 0.79 |
| Peter Pirolli | 3 | 3661 | 538.83 |
| Wai-Tat Fu | 4 | 796 | 73.04 |