Cited by 21Sentiment Analysis and Opinion MiningComputational and Text Analysis MethodsEthics and Social Impacts of AI

External validity of sentiment mining reports: can current methods identify demographic biases, event biases, and manipulation of reviews?

Wijnhoven, Fons, Bloemen, Oscar·2014·Decision Support Systems

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Crossref · 10.1016/j.dss.2013.12.005

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4 of 4 references verified0 citation errors · 0 not checkable

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  • Effects observed on a social platform may manifest differently on other platforms due to different functionalities, communities, or cultural norms.

    “For example, effects observed on a social platform may manifest differently on other platforms due to different functionalities, communities, or cultural norms (Wijnhoven and Bloemen, 2014; Malik and Pfeffer, 2016).”

    From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Wijnhoven and Bloemen, 2014

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Authors
Wijnhoven, F., & Bloemen, O.
Affiliations
University of Twente (NL)
Corresponding author
Wijnhoven, Fons
Venue
Decision Support Systems
Publisher
Elsevier BV
Published
2014-03
Volume
59
Pages
262-273
ISSN
0167-9236 (ISSN-L)
OpenAlex
W2022399093
Cited by
21
References
4
Citations by year
2024: 2 · 2023: 1 · 2021: 1 · 2020: 3 · 2019: 2 · 2018: 2 · 2017: 3 · 2016: 3 · 2015: 3 · 2014: 1
FWCI
2.58
Type
journal article
Language
en
Open access
closed
Locations
  • Decision Support Systems (publishedVersion)
  • University of Twente Research Information (publishedVersion)
  • University of Twente Research Information (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Social Sciences › General Social Sciences › Computational and Text Analysis Methods
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
sentiment analysis, generalizability, demographic bias, review manipulation, user-generated content, stylometry, Goodreads, kernel theory, bias detection

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