bookmarks (hide)6
- BBC News forum posts: 2,594,745 comments from selected BBC News forums and > 1,000 human classified sentiment strengths with a postive strength of 1-5 and a negative strength of 1-5. The classification is the average of three human classifiers. Digg post comments: 1,646,153 comments on Digg posts (typically highlighting news or technology stories) and > 1,000 human classified sentiment strengths with a postive strength of 1-5 and a negative strength of 1-5. The classification is the average of three human classifiers. MySpace (social network site) comments: six sets of systematic samples (3 for the US and 3 for the UK) of all comments exchanged between pairs of friends (about 350 pairs for each UK sample and about 3,500 pairs for each US sample) from a total of >100,000 members and > 1,000 human classified sentiment strengths with a postive strength of 1-5 and a negative strength of 1-5. The classification is the average of three human classifiers.
- SenticNet is a publicly available semantic and affective resource for concept-level opinion mining and sentiment analysis.
- Links to classic papers on unsupervised sentiment analysis. Using methods as pmi, wordnet and LDA.
- SentiStrength estimates the strength of positive and negative sentiment in short texts, even for informal language. It has human-level accuracy for short social web texts in English, except political texts.
publications (hide)7
- (2010)
- Proceedings of the International Conference on Weblogs and Social Media (ICWSM), (2007)
- (2006)
- Data Mining and Knowledge Discovery, (October 2011)
- Handbook of Natural Language Processing, (2010)
- Information Retrieval, 2 (1-2): 1--135 (2008)
- Foundations and Trends® in Information Retrieval, 2 (1-2): 1-135 (2008)
