Information produced and shared on social networks constitute a valuable source for inferring trends and events in the real world. In this paper we show how this can be exploited concretely through quantitative analysis of social content. We present an analysis of the statistical correlation between the security prices of some IT companies and the performance polarity of the same companies as expressed in tweets. Companies’ performance polarities are obtained by applying Conditional Random Fields to the considered streams of tweets. An evaluation of both the classification model and the performed regression analysis is also presented
Shabunina, E. (2015). Correlation between Stock Prices and polarity of companies’ performance in Tweets: a CRF-based Approach.. Intervento presentato a: First International Symposium on Web Algorithms, iSWAG’15, Deauville, Normandy, France.
Correlation between Stock Prices and polarity of companies’ performance in Tweets: a CRF-based Approach.
SHABUNINA, E.
2015
Abstract
Information produced and shared on social networks constitute a valuable source for inferring trends and events in the real world. In this paper we show how this can be exploited concretely through quantitative analysis of social content. We present an analysis of the statistical correlation between the security prices of some IT companies and the performance polarity of the same companies as expressed in tweets. Companies’ performance polarities are obtained by applying Conditional Random Fields to the considered streams of tweets. An evaluation of both the classification model and the performed regression analysis is also presented
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