Name
Title | ||
|---|---|---|
Tweet Enrichment for Effective Dimensions Classification in Online Reputation Management. |
Abstract | ||
|---|---|---|
Online Reputation Management (ORM) is concerned with the monitoring of public opinions on social media for entities such as commercial organisations. In particular, we investigate the task of reputation dimension classification, which aims to classify tweets that mention a business entity into different dimensions (e.g. financial performanceu0027u0027 or products and servicesu0027u0027). However, producing a general reputation dimension classification system that can be used across businesses of different types is challenging, due to the brief nature of tweets and the lack of terms in tweets that relate to specific reputation dimensions. To tackle these issues, we propose a robust and effective tweet enrichment approach that expands tweets with additional discriminative terms from a contemporary Web corpus. Using the RepLab 2014 test collection, we show that our tweet enrichment approach outperforms effective baselines including the top performing submission to RepLab 2014. Moreover, we show that the achieved accuracy scores are very close to the upper bound that our approach could achieve on this collection. |
Year | Venue | Field |
|---|---|---|
2015 | ICWSM | Data mining,Internet privacy,Social media,Query expansion,Computer science,Baseline (configuration management),Discriminative model,Financial performance,Reputation management,Reputation |
DocType | Citations | PageRank |
Conference | 1 | 0.35 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Graham McDonald | 1 | 43 | 7.49 |
| Romain Deveaud | 2 | 61 | 11.03 |
| Richard Mccreadie | 3 | 403 | 32.43 |
| Craig Macdonald | 4 | 2588 | 178.50 |
| Iadh Ounis | 5 | 3438 | 234.59 |