Empath: Understanding Topic Signals in Large-Scale Text
arXiv:1602.06979 · doi:10.1145/2858036.2858535
Abstract
Human language is colored by a broad range of topics, but existing text analysis tools only focus on a small number of them. We present Empath, a tool that can generate and validate new lexical categories on demand from a small set of seed terms (like "bleed" and "punch" to generate the category violence). Empath draws connotations between words and phrases by deep learning a neural embedding across more than 1.8 billion words of modern fiction. Given a small set of seed words that characterize a category, Empath uses its neural embedding to discover new related terms, then validates the category with a crowd-powered filter. Empath also analyzes text across 200 built-in, pre-validated categories we have generated from common topics in our web dataset, like neglect, government, and social media. We show that Empath's data-driven, human validated categories are highly correlated (r=0.906) with similar categories in LIWC.
CHI: ACM Conference on Human Factors in Computing Systems 2016
References in corpus (6)
- Distributed Representations of Words and Phrases and their Compositionality
- Thumbs up? Sentiment Classification using Machine Learning Techniques
- Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
- Finding Deceptive Opinion Spam by Any Stretch of the Imagination
- Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena
- Augur: Mining Human Behaviors from Fiction to Power Interactive Systems
Cited by in corpus (39)
- A Benchmark Study of Machine Learning Models for Online Fake News Detection
- Measuring Emotions in the COVID-19 Real World Worry Dataset
- How we do things with words: Analyzing text as social and cultural data
- Analyzing Right-wing YouTube Channels: Hate, Violence and Discrimination
- Emotion Detection for Misinformation: A Review
- Analyzing the hate and counter speech accounts on Twitter
- Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora
- A Multimodal Framework for Depression Detection during Covid-19 via Harvesting Social Media: A Novel Dataset and Method
- "Like Sheep Among Wolves": Characterizing Hateful Users on Twitter
- Ten Social Dimensions of Conversations and Relationships
- Close-up and Whispering: An Understanding of Multimodal and Parasocial Interactions in YouTube ASMR videos
- Iris: A Conversational Agent for Complex Tasks
- United States Politicians' Tone Became More Negative with 2016 Primary Campaigns
- Characterizing Vaccination Movements on YouTube in the United States and Brazil
- Tending Unmarked Graves: Classification of Post-mortem Content on Social Media
- Who is Addressed in this Comment? Automatically Classifying Meta-Comments in News Comments
- Capturing social media expressions during the COVID-19 pandemic in Argentina and forecasting mental health and emotions
- More than Meets the Tie: Examining the Role of Interpersonal Relationships in Social Networks
- Mining Trends of COVID-19 Vaccine Beliefs on Twitter with Lexical Embeddings
- Identifying Experts in Question & Answer Portals: A Case Study on Data Science Competencies in Reddit
- Modeling Political Activism around Gun Debate via Social Media
- Curatr: A Platform for Semantic Analysis and Curation of Historical Literary Texts
- Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach
- A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts
- Characterizing the public perception of WhatsApp through the lens of media
- Social Catalysts: Characterizing People Who Spark Conversations Among Others
- Quasi-experimental Designs for Assessing Response on Social Media to Policy Changes
- Understanding how social discussion platforms like Reddit are influencing financial behavior
- How Have We Reacted To The COVID-19 Pandemic? Analyzing Changing Indian Emotions Through The Lens of Twitter
- LEXpander: applying colexification networks to automated lexicon expansion
- "I Cannot Do All of This Alone": Exploring Instrumental and Prayer Support in Online Health Communities
- Explaining Outcomes of Multi-Party Dialogues using Causal Learning
- A system for the 2019 Sentiment, Emotion and Cognitive State Task of DARPAs LORELEI project
- Automated Empathy Detection for Oncology Encounters
- Psychometric Analysis and Coupling of Emotions Between State Bulletins and Twitter in India during COVID-19 Infodemic
- Assessing Viewer's Mental Health by Detecting Depression in YouTube Videos
- A Process-driven View on Summative Evaluation of Visual Analytics Solutions
- Augmented Understanding and Automated Adaptation of Curation Rules
- Uncovering Implicit Gender Bias in Narratives through Commonsense Inference