Abstract
Schwartz (Andrew) [1] argues that inter-disciplinary approaches involving computational linguistics and the social sciences are needed to make sense of big data in social networks. The social psychology tool, the Schwartz (Shalom) Values Model [2] is used here alongside linguistic psychological attribute analysis to investigate a context in 'Twitter'. The topic of the Scottish Independence Referendum (September 18th, 2014) was selected as the context because it divided opinion into camps. This study's main hypothesis is that the camps of contexts can be values-profiled. Secondary hypotheses are: the values profiles correlate with psychological attribute profiles in the different voting camps; and the psychological textual analysis adds a wider psychological dimension to topic modeling in 'Twitter'. The methodology combined two processes: the assignment of values to the camps of the Referendum context using the Schwartz Values Model [2]; and the content analysis of the tweets, using the psychological textual analysis tool, LIWC.
| Original language | English |
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| Title of host publication | Proceedings of the 2015 ACM Web Science Conference |
| Publisher | Association for Computing Machinery |
| ISBN (Print) | 9781450336727 |
| DOIs | |
| Publication status | Published - 28 Jun 2015 |
| Event | 7th ACM Web Science Conference, WebSci 2015 - Oxford, United Kingdom Duration: 28 Jun 2015 → 1 Jul 2015 |
Conference
| Conference | 7th ACM Web Science Conference, WebSci 2015 |
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| Place | United Kingdom |
| City | Oxford |
| Period | 28/06/15 → 1/07/15 |
Research Keywords
- Psychological textual analysis
- Social media analysis
- Topic modeling
- Values analysis