A values and psychological attribute analysis of the Scottish Independence Referendum context in Twitter

Caroline Halcrow, Qingpeng Zhang

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

1 Citation (Scopus)

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 languageEnglish
Title of host publicationProceedings of the 2015 ACM Web Science Conference
PublisherAssociation for Computing Machinery
ISBN (Print)9781450336727
DOIs
Publication statusPublished - 28 Jun 2015
Event7th ACM Web Science Conference, WebSci 2015 - Oxford, United Kingdom
Duration: 28 Jun 20151 Jul 2015

Conference

Conference7th ACM Web Science Conference, WebSci 2015
PlaceUnited Kingdom
CityOxford
Period28/06/151/07/15

Research Keywords

  • Psychological textual analysis
  • Social media analysis
  • Topic modeling
  • Twitter
  • Values analysis

Fingerprint

Dive into the research topics of 'A values and psychological attribute analysis of the Scottish Independence Referendum context in Twitter'. Together they form a unique fingerprint.

Cite this