Name
Abstract | ||
|---|---|---|
While considerable attention has been given to the analysis of texts written by depressed individuals, few studies were interested in evaluating and improving lexical resources for supporting the detection of signs of depression in text.
In this paper, we present a search-based methodology to evaluate existing depression lexica. To meet this aim, we exploit existing resources for depression and language use and we analyze which elements of the lexicon are the most effective at revealing depression symptoms. Furthermore, we propose innovative expansion strategies able to further enhance the quality of the lexica.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s10579-018-9423-1 | language resources and evaluation |
Keywords | Field | DocType |
Depression screening, Depression lexicon, Lexicon evaluation, Lexicon expansion, Text analysis, Natural language processing | Computer science,Exploit,Lexicon,Natural language processing,Artificial intelligence | Journal |
Volume | Issue | ISSN |
54 | 1 | 1574-0218 |
Citations | PageRank | References |
0 | 0.34 | 26 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David E. Losada | 1 | 326 | 40.63 |
| Pablo Gamallo | 2 | 139 | 29.27 |