Sentiment analysis

Traditionally in NLP, sentiment analysis aims to identify the opinion or sentiment of the speaker (writer) toward a certain topic. The increasing availability of massive written tidbits of people everyday life enables the large-scale measurement of people’s mood. Peter Dodds and Christopher M suggested a very simple way to measure happiness from written texts[^1]. This method was used in Twittermood and several other researches[^2]. Facebook is also doing similar measurements[^3][^4]. Positive/negative dichotomy is probably too simplistic[^5].

Regarding Homophily and influence, it was shown that the assortativity of happiness can be measured in online social networks[^6][^7].

Interesting application: food mood: http://www.aaai.org/ocs/index.php/ICWSM/ICWSM12/paper/viewFile/4776/5100

How does sentiment analysis differentiate different domains[^8]?

Review

Methods

Deep learning

Using word2vec or doc2vec

Others

Emoji

People

Tutorial

Projects

Softwares and data

Some examples

Articles

Talks

Companies

References

↑ Peter Sheridan Dodds and Christopher M. Danforth (2010). “Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents”. J. Happiness Stud. 11: 441-456. doi:10.1007/s10902-009-9150-9. http://www.springerlink.com/content/757723154j4w726k/.

↑ Peter Sheridan Dodds et al. (2011). Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter. http://arxiv.org/abs/1101.5120.

↑ “Gross National Happiness”. http://apps.facebook.com/usa_gnh/. Retrieved February 4, 2011.

↑ Adam D. I. Kramer (March 23, 2010). “How Happy Are We?”. http://www.facebook.com/blog.php?post=150162112130. Retrieved February 4, 2011.

↑ “Not All Moods are Created Equal! Exploring Human Emotional States in Social Media”. http://research.microsoft.com/en-us/um/people/munmund/pubs/icwsm_12_1.pdf.

http://arxiv.org/abs/1103.0784

http://arxiv.org/abs/1112.1010

↑ “Crossing Media Streams with Sentiment: Domain Adaptation in Blogs, Reviews and Twitter”. http://www.aaai.org/ocs/index.php/ICWSM/ICWSM12/paper/viewFile/4580/4988.