ArticleProceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing2016
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora.
Article in Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Child-Directed Speech Is Semantically Constrained: Evidence From Metaphoricity and Concreteness.Open mind : discoveries in cognitive science · 2026Article
- Changes in Mental State for Help-Seekers of Lifeline Australia's Online Chat Service: Lexical Analysis Approach.JMIR formative research · 2025Article
- The linguistic and emotional effects of weather on UK social media users.Scientific reports · 2025Article
- Moral Association Graph: A Cognitive Model for Automated Moral Inference.Topics in cognitive science · 2025Article
- Article
- Text Mining Oral Histories in Historical Archaeology.International journal of historical archaeology · 2023Article
- Valence norms for 3,600 English words collected during the COVID-19 pandemic: Effects of age and the pandemic.Behavior research methods · 2022Article
- Evaluating criminal justice reform during COVID-19: The need for a novel sentiment analysis package.PLOS digital health · 2022Article
- Cover papers of top journals are reliable source for emerging topics detection: a machine learning based prediction framework.Scientometrics · 2022Article
- Two is better than one: Using a single emotion lexicon can lead to unreliable conclusions.PloS one · 2022Article
- Quantifying the Severity of Adverse Drug Reactions Using Social Media: Network Analysis.Journal of medical Internet research · 2021Article
- Using General-purpose Sentiment Lexicons for Suicide Risk Assessment in Electronic Health Records: Corpus-Based Analysis.JMIR medical informatics · 2021Article
- Tracking COVID-19 Discourse on Twitter in North America: Infodemiology Study Using Topic Modeling and Aspect-Based Sentiment Analysis.Journal of medical Internet research · 2021Article
- Augmenting Semantic Lexicons Using Word Embeddings and Transfer Learning.Frontiers in artificial intelligence · 2021Article
- Assessing Lexical Psychological Properties in Second Language Production: A Dynamic Semantic Similarity Approach.Frontiers in psychology · 2021Article
- BengSentiLex and BengSwearLex: creating lexicons for sentiment analysis and profanity detection in low-resource Bengali language.PeerJ. Computer science · 2021Article
- Automatic Construction of a Depression-Domain Lexicon Based on Microblogs: Text Mining Study.JMIR medical informatics · 2020Article
- Construct validity of six sentiment analysis methods in the text of encounter notes of patients with critical illness.Journal of biomedical informatics · 2019Article
- Machine learning to support social media empowered patients in cancer care and cancer treatment decisions.PloS one · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
A word's sentiment depends on the domain in which it is used. Computational social science research thus requires sentiment lexicons that are specific to the domains being studied. We combine domain-specific word embeddings with a label propagation framework to induce accurate domain-specific sentiment lexicons using small sets of seed words. We show that our approach achieves state-of-the-art performance on inducing sentiment lexicons from domain-specific corpora and that our purely corpus-based approach outperforms methods that rely on hand-curated resources (e.g., WordNet). Using our framework, we induce and release historical sentiment lexicons for 150 years of English and community-specific sentiment lexicons for 250 online communities from the social media forum Reddit. The historical lexicons we induce show that more than 5% of sentiment-bearing (non-neutral) English words completely switched polarity during the last 150 years, and the community-specific lexicons highlight how sentiment varies drastically between different communities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.