# Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora

arXiv: https://arxiv.org/abs/1606.02820 · HTML: https://mlsanity.com/paper/1606.02820/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jun 2016.

## Built on by (most cited first, 19 of 19)

- [Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus](https://mlsanity.com/paper/2104.08758/) (2021)
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- [Building Knowledge-Guided Lexica to Model Cultural Variation](https://mlsanity.com/paper/2406.11622/) (2024)
- [Summarising Historical Text in Modern Languages](https://mlsanity.com/paper/2101.10759/) (2021)
- [SWEAT: Scoring Polarization of Topics across Different Corpora](https://mlsanity.com/paper/2109.07231/) (2021)
- [Sentiment Analysis in Finance: From Transformers Back to eXplainable Lexicons (XLex)](https://mlsanity.com/paper/2306.03997/) (2023)
- [Survey in Characterizing Semantic Change](https://mlsanity.com/paper/2402.19088/) (2024)
- [Capturing Stance Dynamics in Social Media: Open Challenges and Research Directions](https://mlsanity.com/paper/2109.00475/) (2021)
- [COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities](https://mlsanity.com/paper/2209.06470/) (2022)
- [AQuilt: Weaving Logic and Self-Inspection into Low-Cost, High-Relevance Data Synthesis for Specialist LLMs](https://mlsanity.com/paper/2507.18584/) (2025)
- [FinGPT: Enhancing Sentiment-Based Stock Movement Prediction with Dissemination-Aware and Context-Enriched LLMs](https://mlsanity.com/paper/2412.10823/) (2024)
- [Augmenting semantic lexicons using word embeddings and transfer learning](https://mlsanity.com/paper/2109.09010/) (2021)
- [Modular Domain Adaptation](https://mlsanity.com/paper/2204.14213/) (2022)
- [Beyond Labels: Information-Efficient Human-in-the-Loop Learning using Ranking and Selection Queries](https://mlsanity.com/paper/2602.15738/) (2026)
- [Curatr: A Platform for Semantic Analysis and Curation of Historical Literary Texts](https://mlsanity.com/paper/2306.08020/) (2023)
- [CIDER: Context sensitive sentiment analysis for short-form text](https://mlsanity.com/paper/2307.07864/) (2023)
- [The Language of Weather: Social Media Reactions to Weather Accounting for Climatic and Linguistic Baselines](https://mlsanity.com/paper/2407.07683/) (2024)

## Abstract (arXiv)

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, achieving state-of-the-art performance competitive with approaches that rely on hand-curated resources. Using our framework we perform two large-scale empirical studies to quantify the extent to which sentiment varies across time and between communities. 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 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.