ReviewFrontiers in artificial intelligence2020
How We Do Things With Words: Analyzing Text as Social and Cultural Data.
Review in Frontiers in artificial intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed.
- Quantifying Global Foreign Affairs with a Multimodal Dataset of Diplomatic Websites.Scientific data · 2025Article
- Can deepfakes be used to study emotion perception? A comparison of dynamic face stimuli.Behavior research methods · 2024Article
- IRMA: the 335-million-word Italian coRpus for studying MisinformAtion.Proceedings of the conference. Association for Computational Linguistics. Meeting · 2023Article
- Pandemic news information uncertainty-News dynamics mirror differential response strategies to COVID-19.PloS one · 2023Article
- Critical reflections on three popular computational linguistic approaches to examine Twitter discourses.PeerJ. Computer science · 2023Article
- On the use of sentiment analysis for linguistics research. Observations on sentiment polarity and the use of the progressive in Italian.Frontiers in artificial intelligence · 2023Article
- Interconnectedness and (in)coherence as a signature of conspiracy worldviews.Science advances · 2022Article
- LOCO: The 88-million-word language of conspiracy corpus.Behavior research methods · 2022Article
- Exploring the Integration of Engineering Design Practices in Tenth-Grade Chemistry Activities.Frontiers in psychology · 2022Article
- Essay content and style are strongly related to household income and SAT scores: Evidence from 60,000 undergraduate applications.Science advances · 2021Article
- TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora.Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting · 2021Article
- A Spatial-Temporal Model for Event Detection in Social Media.Procedia computer science · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this article we describe our experiences with computational text analysis involving rich social and cultural concepts. We hope to achieve three primary goals. First, we aim to shed light on thorny issues not always at the forefront of discussions about computational text analysis methods. Second, we hope to provide a set of key questions that can guide work in this area. Our guidance is based on our own experiences and is therefore inherently imperfect. Still, given our diversity of disciplinary backgrounds and research practices, we hope to capture a range of ideas and identify commonalities that resonate for many. This leads to our final goal: to help promote interdisciplinary collaborations. Interdisciplinary insights and partnerships are essential for realizing the full potential of any computational text analysis involving social and cultural concepts, and the more we bridge these divides, the more fruitful we believe our work will be.
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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.