CoChat
Sign Up
Cited by 610Sentiment Analysis and Opinion MiningComputational and Text Analysis MethodsNews Media Framing and Political Communication

The DOI matches its Crossref record; 92 of the 94 references it cites were found in a registry or an index, and 1 are not checked yet.

Affective News: The Automated Coding of Sentiment in Political Texts

Young, Lori, Soroka, Stuart·2012·Political Communication
DOI 10.1080/10584609.2012.671234
Open this paper in CoChat — free account

Abstract

An increasing number of studies in political communication focus on the “sentiment” or “tone” of news content, political speeches, or advertisements. This growing interest in measuring sentiment coincides with a dramatic increase in the volume of digitized information. Computer automation has a great deal of potential in this new media environment. The objective here is to outline and validate a new automated measurement instrument for sentiment analysis in political texts. Our instrument uses a dictionary-based approach consisting of a simple word count of the frequency of keywords in a text from a predefined dictionary. The design of the freely available Lexicoder Sentiment Dictionary (LSD) is discussed in detail here. The dictionary is tested against a body of human-coded news content, and the resulting codes are also compared to results from nine existing content-analytic dictionaries. Analyses suggest that the LSD produces results that are more systematically related to human coding than are results based on the other available dictionaries. The LSD is thus a useful starting point for a revived discussion about dictionary construction and validation in sentiment analysis for political communication.

Overview

Integrity signals

Registry

Crossref · 10.1080/10584609.2012.671234

Cites

92 of 93 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Citations

Cites

Show all 94 references

Research works printed but not linked: 11

  1. Bradley M. M., 1999, Affective Norms for English Words (ANEW): Stimuli, instruction manual and affective ratings
  2. Grefenstette G., 2004, Exploring attitude and affect in text: Theories and applications, 93
  3. Hart R. P., 2000, DICTION 5.0: The text analysis program
  4. Huitt W., 2003, The affective system: Educational psychology interactive
  5. Krueger J. S., 2005, The place of prediction in politics
  6. Mishne G., 2005, Experiments with mood classification in blog posts
  7. Murphy C., 2006, The rhetorical semantics of state ballot initiative arguments in California, 1980–2004
  8. Nussbaum M., 2004, Hiding from humanity: Shame, disgust and the law
  9. Roget P. M., 1911, Roget's thesaurus of English words and phrases (supplemented electronic version)
  10. Tong R., 2001, Detecting and tracking opinions in online discussions
  11. Whissell C., 1989, Emotion: Theory and research, 113

Cited by

Sorted by citations

Items 601–610 of 610

Related

See all

Metadata

Authors
Young, L., & Soroka, S.
Affiliations
  • University of Pennsylvania (US)
  • McGill University (CA)
Corresponding author
Soroka, Stuart
ORCID
Soroka, Stuart
Venue
Political Communication
Publisher
Informa UK Limited
Published
2012-04
Volume
29
Issue
2
Pages
205-231
ISSN
  • 1058-4609 (ISSN-L)
  • 1091-7675
DOI
10.1080/10584609.2012.671234
OpenAlex
W2072514260
Semantic Scholar
fa26c8c77f34e2f500af22f8dbb643fb7654b585
Cited by
609
References
94
Citations by year
2026: 35 · 2025: 46 · 2024: 55 · 2023: 60 · 2022: 53 · 2021: 82 · 2020: 68 · 2019: 56 · 2018: 42 · 2017: 32 · 2016: 19 · 2015: 20 · 2014: 12 · 2013: 26 · 2012: 2
FWCI
19.21
Type
journal article
Language
en
Open access
closed
Locations
Political Communication (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Social Sciences › General Social Sciences › Computational and Text Analysis Methods
  • Social Sciences › Communication › News Media Framing and Political Communication
Keywords
sentiment analysis, lexicon-based sentiment analysis, political news, computational text analysis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review