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
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
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Prospect theory: An analysis of decision under risk
Kahneman, D. J., & Tversky, A. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511609220.014 · Cited by 32,720
(1994) · DigitalGeorgetown (Georgetown University Library) · Cited by 10,542
Text categorization with Support Vector Machines: Learning with many relevant features
Joachims, T. (1998) · Lecture notes in computer science · doi:10.1007/bfb0026683 · Cited by 8,271
DESCARTES' ERROR: Emotion, Reason, and the Human Brain
Marg, E. (1995) · Optometry and Vision Science · doi:10.1002/j.1538-9235.1995.tb03988.x · Cited by 8,178
Thumbs up?: sentiment classification using machine learning techniques
Pang, B., Lee, L., & Vaithyanathan, S. (2002) · Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02 · doi:10.3115/1118693.1118704 · Cited by 7,024
Landauer, T. K., & Dumais, S. T. (1997) · Psychological Review · doi:10.1037/0033-295x.104.2.211 · Cited by 6,282
(1996) · Cited by 3,692
Recognizing contextual polarity in phrase-level sentiment analysis
Wilson, T., Wiebe, J., & Hoffmann, P. (2005) · doi:10.3115/1220575.1220619 · Cited by 3,388
Psychological Aspects of Natural Language Use: Our Words, Our Selves
Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G. (2003) · Annual Review of Psychology · doi:10.1146/annurev.psych.54.101601.145041 · Cited by 2,624
Research works printed but not linked: 11
- Bradley M. M., 1999, Affective Norms for English Words (ANEW): Stimuli, instruction manual and affective ratings
- Grefenstette G., 2004, Exploring attitude and affect in text: Theories and applications, 93
- Hart R. P., 2000, DICTION 5.0: The text analysis program
- Huitt W., 2003, The affective system: Educational psychology interactive
- Krueger J. S., 2005, The place of prediction in politics
- Mishne G., 2005, Experiments with mood classification in blog posts
- Murphy C., 2006, The rhetorical semantics of state ballot initiative arguments in California, 1980–2004
- Nussbaum M., 2004, Hiding from humanity: Shame, disgust and the law
- Roget P. M., 1911, Roget's thesaurus of English words and phrases (supplemented electronic version)
- Tong R., 2001, Detecting and tracking opinions in online discussions
- Whissell C., 1989, Emotion: Theory and research, 113
Cited by
Sorted by citations
Items 501–600 of 610
The Role of Ecb Speeches in Nowcasting German Gdp
Koçak, N. A. (2020) · European Financial and Accounting Journal · doi:10.18267/j.efaj.241
Effects of Social Media on the Migrant Image Formation
Komarova, E. V. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-65857-1_32
Content Analysis of Hospital Reviews From Differing Sources: Does Review Source Matter?
Islam, S., Mir, S., Defina, C., & Silva, C. (2021) · Journal of Excellence in Nursing and Healthcare Practice · doi:10.5590/jswgc.2021.3.1.01
Small NGOs in Global Governance: Agenda Setting in the Governance of Biodiversity and Wildlife
Shibaike, T. (2020) · TSpace (University of Toronto)
Modern Survey Estimation with Social Media and Auxiliary Data
Ferg, R. A. (2020) · Deep Blue (University of Michigan)
Political Platforms: Technology, User Affordances, and Campaign Communications
Hiaeshutter-Rice, D. (2020) · Deep Blue (University of Michigan)
Monitoring of the Last US Presidential Elections
Glauser, C., Savoy, J., & Schmid, L. (2021) · International Journal of Computer Science and Information Technology · doi:10.5121/ijcsit.2021.13203
Understanding public policy through mass media
Lawlor, A. (2014) · eScholarship@McGill (McGill) · doi:10.82308/34924
Sentiment and Uncertainty About RegulationPreprint
Sinclair, T. M., & Xie, Z. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4651174
Presidential Calls to Congress
Collins, P. M., & Eshbaugh‐Soha, M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108682428.006
Schwartz, F. P. (2021) · Editora Metrics eBooks · doi:10.46550/978-65-89700-34-0.587-588
Going Public on Supreme Court Cases before the Modern Presidency
Collins, P. M., & Eshbaugh‐Soha, M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108682428.009
Bleich, E., & van der Veen, M. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.003.0007
What do newspapers talk about when they talk about Muslims?
Bleich, E., & van der Veen, M. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.003.0006
United States newspaper coverage of Muslims
Bleich, E., & van der Veen, M. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.003.0003
Bleich, E., & van der Veen, M. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.003.0005
Bleich, E., & van der Veen, M. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.003.0002
Bleich, E., & van der Veen, M. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.003.0004
Collins, P. M., & Eshbaugh‐Soha, M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108682428.013
Collins, P. M., & Eshbaugh‐Soha, M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108682428.010
Collins, P. M., & Eshbaugh‐Soha, M. (2019) · doi:10.1017/9781108682428.001
Independent Media Under Pressure: Evidence from RussiaPreprint
Paskhalis, T., Rosenfeld, B. R. M., & Tertytchnaya, K. (2021) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/pz68w
Independent Media Under Pressure: Evidence from RussiaPreprint
Paskhalis, T., Rosenfeld, B. R. M., & Tertytchnaya, K. (2021) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/m6ur4
(2019) · Cambridge University Press eBooks · doi:10.1017/9781108682428.012
Collins, P. M., & Eshbaugh‐Soha, M. (2019) · doi:10.1017/9781108682428.011
World Bank East Asia and Pacific Economic Update, April 2019: Managing Headwinds
Bank, W. (2019) · World Bank, Washington, DC eBooks · doi:10.1596/978-1-4648-1412-9
Soziale Medien in der empirischen Forschung
Zeller, F. (2015) · Springer eBooks · doi:10.1007/978-3-658-03895-3_21-1
(2013) · Les Presses de l'Université de Montréal eBooks · doi:10.4000/books.pum.5929
(2013) · Les Presses de l'Université de Montréal eBooks · doi:10.4000/books.pum.5931
(2013) · Les Presses de l'Université de Montréal eBooks · doi:10.4000/books.pum.5881
Kelm, O., Gerl, K., & Meißner, F. (2022) · Springer eBooks · doi:10.1007/978-3-658-26233-4_55
Soziale Medien in der empirischen Forschung
Zeller, F. (2022) · Springer eBooks · doi:10.1007/978-3-658-25995-2_21
Lai, R. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4418488
THE HONECKER AFFAIRE AND THE FALL OF THE BERLIN WALL SEEN FROM AMERICAN NEWSPAPERS
Harvey-Valdés, H. E., & Soto, Á. (2023) · Universum · doi:10.4067/s0718-23762023000100279
Political biases in international organization evaluation reports
Jankauskas, V., & Eckhard, S. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780192855206.003.0006 · Cited by 1
Tincknell, L. (2023) · Queensland University of Technology · doi:10.5204/thesis.eprints.243267
How Presidents Answer the Call of International Capital
Arnold, C., Doyle, D. A., & Wiesehomeier, N. (2023) · Journal of Politics in Latin America · doi:10.1177/1866802x231210581
Presidential candidates nobody wants?
Fazekas, Z., & Hatemi, P. (2023) · Presidential Studies Quarterly · doi:10.1111/psq.12866
Suh, J. J. (2023) · East Asian Economic Review · doi:10.11644/kiep.eaer.2023.27.4.426
Enhancing Financial Sentiment Analysis with a Hybrid Feature Selection Approach
Shams, R., Khosravian, J., Samimi, P., & Saeed, F. (2026) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-032-23021-8_15
Gross, J. H., & Nestor, D. (2024) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780192868282.013.45
The Role of Sentiment in Credit MarketsPreprint
Kabiri, A., Landon‐Lane, J. S., Turton, J., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4795367
Supplementary materials for the analyses in chapters 2–6
Bleich, E., & van der Veen, M. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.005.0003
Corpus collection and methodology
Bleich, E., & van der Veen, M. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.005.0002
Bleich, E., & van der Veen, M. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.002.0003
Bleich, E., & van der Veen, M. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.002.0004
Bleich, E., & van der Veen, M. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.005.0001
Bleich, E., & van der Veen, M. (2022) · Oxford University Press eBooks · doi:10.1093/oso/9780197611715.002.0006
Streamlining Canadian parliamentary data access: A user-friendly R package
Millette, A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0302457
Dictionary-based Sentiment Analysis at Subword Level
Yang, J. (2024) · IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) · doi:10.1109/iaict62357.2024.10617606
Montgomery, J. P. (2024) · University of North Texas Digital Library (University of North Texas) · doi:10.12794/metadc2356179
Do High-Level Visits Reflect Regional Priorities? A Study of U.S. News Media Data
Aras, B., & DAĞCI, K. (2024) · Alternatives Global Local Political · doi:10.1177/03043754241299085
A reputação do Brasil pela mídia internacional
Cordeiro, F. B. L. (2024) · doi:10.11606/d.8.2024.tde-15012025-184048
Partisan Media Coverage of Abortion Policy
Graciano, J. (2022) · doi:10.12794/metadc2048634
Introduction to the Special Issue on “Text as Data in the Study of Politics in Developing Countries”
Kikuchi, H., & Kubo, K. (2025) · The Developing Economies · doi:10.1111/deve.12432
Lai, R. (2025) · Political Science Research and Methods · doi:10.1017/psrm.2025.5
Bengali Cyberbullying: Detection, Categorization, and Gender Bias Analysis
Hossain, M. M., Hossain, M. S., Chaki, S., et al. (2024) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw65004.2024.00027
Karolak, M., Hussain, M., & Marir, F. (2025) · Journal of Contemporary African Studies · doi:10.1080/02589001.2025.2474435
Capturing the Fourth Estate: Government Influence on US Newspaper Coverage of Foreign Leaders
Lai, R. (2025) · British Journal of Political Science · doi:10.1017/s0007123424000991
Buyens, W. (2025) · The International Journal of Press/Politics · doi:10.1177/19401612251334941
Corpus-Based Exploration of Defense-Related Political Speeches
Ivanović, M., & Kocijan, K. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-89810-5_8
Financial and Accounting Dictionaries for Text Mining
Tsoutsa, P., Solomos, K., Fitsilis, P., et al. (2024) · doi:10.1145/3716554.3716606
Metodologias de análise das emoções
Hauber, G., & Maia, R. C. M. (2022) · EDUFBA eBooks · doi:10.7476/9786556308883.0007
Legislation and Party Politics in the Japanese Diet:
Imoto, T. (2024) · The Annuals of Japanese Political Science Association · doi:10.7218/nenpouseijigaku.75.1_217
Guedes-Neto, J. V., & Honeker, A. (2025) · Electoral Studies · doi:10.1016/j.electstud.2025.102952
Detecting Formatted Text: Data Collection Using Computer Vision
Colner, J. (2025) · Political Analysis · doi:10.1017/pan.2025.10006
Kenwick, M., Lee, S., & Kolcak, B. (2025) · Journal of Conflict Resolution · doi:10.1177/00220027251365535
Reveilhac, M., & Schneider, G. (2025) · International Journal of Corpus Linguistics · doi:10.1075/ijcl.24132.rev
From Fear to Compassion: Dual Populisms and Syria’s Displaced in Turkey’s 2023 Elections
Fatehi, E. (2025) · Journal of Intercultural Studies · doi:10.1080/07256868.2025.2556397
Quantifying Global Foreign Affairs with a Multimodal Dataset of Diplomatic Websites
Muğurtay, N., Şirin, K. G., Najafabad, M. H., Kahya, A. T., Yılmaz, F. G., Zouzou, Y., Bahçeci, B., Demir, A., Tosun, D., Müftüler‐Baç, M., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-06334-5
How Can We Size Your Core Issue? Assessing Salience Validity Using Psychophysiology
Tremblay‐Antoine, C., Dufresne, Y., & Vachon, F. (2025) · Public Opinion Quarterly · doi:10.1093/poq/nfaf041
Park, J. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-26629-4.00222-7
International relations measurement
Muzas, B. K. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-26629-4.00209-4
Technocrats, Reputation, and Responsiveness in Policy Explanation
di Vettimo, M. S., & Koop, C. E. (2025) · Governance · doi:10.1111/gove.70103
Extremists on the Left and Right Use Angry, Negative LanguagePreprint
Melton, Z. J., Brandt, M., Frimer, J. A., & Motyl, M. S. (2018) · OSF Preprints (OSF Preprints)
Topic Augmented Media Sentiment Indices (TaMSI): BER (Stellenbosch) Media Sentiment Index
Odendaal, H. (2025) · Journal of Business Cycle Research · doi:10.1007/s41549-025-00118-x
Stout, C. T., Phoenix, D. L., Leslie, G., & Schroeder, E. (2025) · Political Psychology · doi:10.1111/pops.70102
The gender gap in language emotionality: a focus on the Italian parliament (1948–2020)
Decadri, S., & Pagano, G. (2026) · Quality & Quantity · doi:10.1007/s11135-025-02536-6
Wilbur, D. (2026) · Small Wars and Insurgencies · doi:10.1080/09592318.2026.2616359
Roedenbeck, M., & Herold, M. (2026) · SAGE Open · doi:10.1177/21582440251410723
Eisele, O., Heidenreich, T., & Maares, P. (2026) · European Journal of Political Research · doi:10.1017/s1475676526100668
Soroka, S., & Wlezien, C. B. (2026) · Political Communication · doi:10.1080/10584609.2026.2613647
Self-citationEconomic Benefactor or Risky Dependence? Ambivalence in China–Brazil Agribusiness Ties
Abelin, P. H., & Pearson, M. M. (2026) · Journal of Politics in Latin America · doi:10.1177/1866802x261434254
Tsagkroni, V., & Bara, J. L. (2026) · Political Science · doi:10.1080/00323187.2026.2650284
A Conceptual Reappraisal of Chinese Deliberative Democracy (Xieshang Minzhu 协商民主)
Li, R. (2021) · theses.fr (ABES) · doi:10.70675/7bd60ec2z27b7z4820zb2d9z95ecd7533250
Climate Change and Terrorism News: Similar or Different?
Hoffman, A. M., & Jengelley, D. H. A. (2026) · American Politics Research · doi:10.1177/1532673x261443523
An Overview of Media Coverage Shifts Before and After the 2024 U.S. Presidential Election
Lokmanoglu, A. D., Gupta, A., Hemmila, T., Jadoon, A., Knijnenburg, B. P., & Perliger, A. (2026) · Journal of Political Marketing · doi:10.1080/15377857.2026.2667146
Bread, Butter, and Bias: How News Coverage of Egg Price and Tariffs Polarizes U.S. Democracy?
Zhong, B., Zhu, Y., Wang, N., Wang, S., Xu, J., Yi, H., Lim, H. H., & Feng, G. C. (2026) · American Behavioral Scientist · doi:10.1177/00027642261450672
Learning to Disagree: Descriptive and Prescriptive Convergence in AI GovernancePreprint
Canfil, J. K. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6850598
Mitsui, C., & Kawamura, Y. (2026) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2026.100331
Bayram, İ., & Uğur, N. G. (2026) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2026.104937
How do EBA stress tests affect financial stability? Evidence from media coverage
de Comères, Q. B. (2026) · Journal of international financial markets, institutions, and money · doi:10.1016/j.intfin.2026.102371
Jablow, Z., & Althaus, S. L. (2026) · Public Opinion Quarterly · doi:10.1093/poq/nfag055
Wirkungen politischer Kommunikation
Lübke, S., & Haßler, J. (2026) · Springer eBooks · doi:10.1007/978-3-658-46851-4_20-1
Depicting Democracy as Chaos: An Analysis of International News in Chinese Media
Zhou, Y. (2026) · Mass Communication & Society · doi:10.1080/15205436.2026.2707474
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
- 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
