Name
Abstract | ||
|---|---|---|
Abstract Understanding the landscape of opinions on a given topic or issue is important for policy makers, sociologists, and intelligence analysts. The first step in this process is to retrieve relevant opinions. Discussion forums are potentially a good source of this information, but comes with a unique set of retrieval challenges. In this short paper, we test a range of existing techniques for forum retrieval and develop new retrieval models to differentiate between opinionated and factual forum posts. We are able to demonstrate some significant performance improvements over the baseline retrieval models, demonstrating that this as a promising avenue for further study. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2505515.2507861 | CIKM |
Keywords | Field | DocType |
retrieval challenge,factual forum post,promising avenue,new retrieval model,good source,baseline retrieval model,policy maker,intelligence analyst,retrieving opinion,forum retrieval,discussion forum,social media | Data mining,World Wide Web,Social media,Information retrieval,Computer science | Conference |
Citations | PageRank | References |
1 | 0.34 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laura Dietz | 1 | 339 | 28.86 |
| Ziqi Wang | 2 | 47 | 4.63 |
| Samuel Huston | 3 | 84 | 3.75 |
| W. Bruce Croft | 4 | 17812 | 2796.94 |