A new ANEW: Evaluation of a word list for sentiment analysis in microblogs |
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Abstract | Sentiment analysis of microblogs such as Twitter has recently gained a fair amount of attention. One of the simplest sentiment analysis approaches compares the words of a posting against a labeled word list, where each word has been scored for valence, -- a "sentiment lexicon" or "affective word lists". There exist several affective word lists, e.g., ANEW (Affective Norms for English Words) developed before the advent of microblogging and sentiment analysis. I wanted to examine how well ANEW and other word lists performs for the detection of sentiment strength in microblog posts in comparison with a new word list specifically constructed for microblogs. I used manually labeled postings from Twitter scored for sentiment. Using a simple word matching I show that the new word list may perform better than ANEW, though not as good as the more elaborate approach found in SentiStrength. |
Keywords | sentiment analysis, Twitter, ANEW |
Type | Conference paper [With referee] |
Conference | Making Sense of Microposts Workshop (MSM 2011) |
Year | 2011 Month March |
Publisher | Informatics and Mathematical Modelling, Technical University of Denmark |
Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby |
Electronic version(s) | [pdf] |
BibTeX data | [bibtex] |
IMM Group(s) | Intelligent Signal Processing |