ArticleSociological methods & research2017
Using Twitter for Demographic and Social Science Research: Tools for Data Collection and Processing.
Article in Sociological methods & research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed.
- Bridging functional bionanomaterials and the clinic: strategic communication as a translational enabler.Journal of nanobiotechnology · 2026Review
- Spatial patterns of foreign agricultural land holdings near U.S. military interest points.PloS one · 2026Article
- Examination of social media nutrition information related to multiple sclerosis: a cross-sectional social network analysis.Public health nutrition · 2025Article
- Unveiling Global Narratives of Restoration Policy: Big Data Insights into Competing Framings and Implications.Geoforum; journal of physical, human, and regional geosciences · 2025Article
- "ChatGPT says no": agency, trust, and blame in Twitter discourses after the launch of ChatGPT.AI and ethics · 2025Article
- Tracking the Spread of Pollen on Social Media Using Pollen-Related Messages From Twitter: Retrospective Analysis.Journal of medical Internet research · 2024Article
- Place branding: Religion in shaping the three-dimensional essence of a city brand through stakeholder engagement.PloS one · 2024Article
- Characterizing the Discourse of Popular Diets to Describe Information Dispersal and Identify Leading Voices, Interaction, and Themes of Mental Health: Social Network Analysis.JMIR infodemiology · 2023Article
- The Public Health Contribution of Sentiment Analysis of Monkeypox Tweets to Detect Polarities Using the CNN-LSTM Model.Vaccines · 2023Article
- Sampling Twitter users for social science research: evidence from a systematic review of the literature.Quality & quantity · 2023Article
- "The algorithm will screw you": Blame, social actors and the 2020 A Level results algorithm on Twitter.PloS one · 2023Article
- Critical reflections on three popular computational linguistic approaches to examine Twitter discourses.PeerJ. Computer science · 2023Article
- Exploring the Factors Associated with Mental Health Attitude in China: A Structural Topic Modeling Approach.International journal of environmental research and public health · 2022Article
- The Associations Between Racially/Ethnically Stratified COVID-19 Tweets and COVID-19 Cases and Deaths: Cross-sectional Study.JMIR formative research · 2022Article
- Methods to Establish Race or Ethnicity of Twitter Users: Scoping Review.Journal of medical Internet research · 2022Article
- Bodies-in-waiting as infrastructure: Assembling the Philippine Government's disciplinary quarantine response to COVID-19.Social science & medicine (1982) · 2022Article
- Topic modeling and sentiment analysis of Chinese people's attitudes toward volunteerism amid the COVID-19 pandemic.Frontiers in psychology · 2022Article
- Bullying-Related Tweets: a Qualitative Examination of Perpetrators, Targets, and Helpers.International journal of bullying prevention : an official publication of the International Bullying Prevention Association · 2022Article
- Social Media Big Data Analysis: Towards Enhancing Competitiveness of Firms in a Post-Pandemic World.Journal of healthcare engineering · 2022Article
- "It's a stomachache filled with stress": Tracing the Uneven Spillover Effects of Racialized Police Violence Using Twitter Data.Currents · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Despite recent and growing interest in using Twitter to examine human behavior and attitudes, there is still significant room for growth regarding the ability to leverage Twitter data for social science research. In particular, gleaning demographic information about Twitter users-a key component of much social science research-remains a challenge. This article develops an accurate and reliable data processing approach for social science researchers interested in using Twitter data to examine behaviors and attitudes, as well as the demographic characteristics of the populations expressing or engaging in them. Using information gathered from Twitter users who state an intention to not vote in the 2012 presidential election, we describe and evaluate a method for processing data to retrieve demographic information reported by users that is not encoded as text (e.g., details of images) and evaluate the reliability of these techniques. We end by assessing the challenges of this data collection strategy and discussing how large-scale social media data may benefit demographic researchers.
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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.