Journal
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
Volume 95, Issue -, Pages 96-108Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2013.04.013
Keywords
Opinion mining; Sentiment analysis; Text mining; Social media analysis; Machine learning; Conversation analysis; Membership categorization analysis
Categories
Funding
- Economic and Social Research Council under the Digital Social Research Demonstrator Programme [ES/J009903/1]
- COSMOS - Joint Information Systems Committee (JISC) under the Digital Infrastructure Research Programme
- Economic and Social Research Council [ES/J009903/1] Funding Source: researchfish
- ESRC [ES/J009903/1] Funding Source: UKRI
Ask authors/readers for more resources
The growing number of people using social media to communicate with others and document their personal opinion and action is creating a significant stream of data that provides the opportunity for social scientists to conduct online forms of research, providing an insight into online social formations. This paper investigates the possibility of forecasting spikes in social tension - defined by the UK police service as any incident that would tend to show that the normal relationship between individuals or groups has seriously deteriorated - through social media. A number of different computational methods were trialed to detect spikes in tension using a human coded sample of data collected from Twitter, relating to an accusation of racial abuse during a Premier League football match. Conversation analysis combined with syntactic and lexicon-based text mining rules; sentiment analysis; and machine learning methods was tested as a possible approach. Results indicate that a combination of conversation analysis methods and text mining outperforms a number of machine learning approaches and a sentiment analysis tool at classifying tension levels in individual tweets. (C) 2013 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available