Name
Abstract | ||
|---|---|---|
The growth of content on the web has been followed by increasing interest in opinion mining. This field of research relies on accurate recognition of emotion from textual data. There's been much research in sentiment analysis lately, but it always focuses on the same elements. Sentiment analysis traditionally depends on linguistic corpora, or common sense knowledge bases, to provide extra dimensions of information to the text being analyzed. Previous research hasn't yet explored a fully automatic method to evaluate how events associated to certain entities may impact each individual's sentiment perception. This project presents a method to assign valence ratings to entities, using information from their Wikipedia page, and considering user preferences gathered from the user's Facebook profile. Furthermore, a new affective lexicon is compiled entirely from existing corpora, without any intervention from the coders. |
Year | Venue | Keywords |
|---|---|---|
2011 | EPIA '89 | user preference,news title,accurate recognition,facebook profile,sentiment perception,wikipedia page,new affective lexicon,automatic method,previous research,certain entity,common sense knowledge base,sentiment analysis |
Field | DocType | Volume |
Data mining,Commonsense knowledge,Information retrieval,Sentiment analysis,Computer science,Lexicon,Natural language processing,Artificial intelligence,Affect (psychology),Perception | Conference | 7026 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.35 |
References | Authors | |
16 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Loureiro | 1 | 1 | 4.07 |
| Goreti Marreiros | 2 | 142 | 39.40 |
| José Neves | 3 | 580 | 75.09 |