Voter Classification Based on Susceptibility to Persuasive Strategies: A Machine Learning Approach


Demir M. O., Simonetti B., BAŞARAN M. A., IRMAK S.

SOCIAL INDICATORS RESEARCH, vol.155, no.1, pp.355-370, 2021 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 155 Issue: 1
  • Publication Date: 2021
  • Doi Number: 10.1007/s11205-020-02605-3
  • Journal Name: SOCIAL INDICATORS RESEARCH
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, FRANCIS, IBZ Online, International Bibliography of Social Sciences, Periodicals Index Online, ABI/INFORM, Abstracts in Social Gerontology, Business Source Elite, Business Source Premier, CAB Abstracts, Communication & Mass Media Index, EBSCO Education Source, EconLit, Geobase, Index Islamicus, Philosopher's Index, Political Science Complete, Psycinfo, Public Administration Abstracts, Public Affairs Index, Social services abstracts, Sociological abstracts, Veterinary Science Database, Worldwide Political Science Abstracts
  • Page Numbers: pp.355-370
  • Keywords: Political marketing, Persuasive strategies, Machine learning, POLITICAL CONSERVATISM, PERSONAL VALUES, ACCOUNTABILITY, CREDIBILITY, COMPLEXITY, ATTITUDES, IDEOLOGY, LIBERALS
  • Akdeniz University Affiliated: Yes

Abstract

The current literature on the campaigns of political marketing is based on mass communication. However, the online community introduces new opportunities, one of them is captology. As a part of captology, the persuasive strategies take increasing attention from both authors and practitioners. There is a growing literature that persuasive technologies are useful in the attitudinal and behavioral change of the targeted group, which is the aim of political marketing. This research introduces the persuasive strategies into political marketing literature. In this manuscript, respondents are discriminated based on their susceptibility to the persuasive strategies to determine which persuasive strategy has effects on liberals and conservative. Findings suggest that liberals and conservatives can be discriminated based on their susceptibility to persuasive strategies using machine learning algorithms. The findings of the study offer new insights into political marketing campaigns.