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metadata language: English

COVID-19 Twitter Dataset with Latent Topics, Sentiments and Emotions Attributes

Version
1
Resource Type
Dataset : other, program source code, text
Creator
  • Yang, Yinping (Dr.)
Publication Date
2020-07-18
Free Keywords
[COVID-19; pandemic; twitter; social media; , COVID-19; pandemic; twitter; social media; sentiment analysis; emotion recognition; ]
Description
  • Abstract

    We collected and processed a dataset and make it available for the research community to study the COVD-19 pandemic in multiple possibilities.
Temporal Coverage
  • 2020-01-28 / 2020-07-01
    Time Period: Tue Jan 28 00:00:00 EST 2020--Wed Jul 01 00:00:00 EDT 2020
Geographic Coverage
  • Global
Sampled Universe
Twitter posts.
Collection Mode
  • This resource describes a large dataset covering over 63 million coronavirus-related Twitter posts from more than 13 million unique users since 28 January to 1 July 2020. As strong concerns and emotions are expressed in the tweets, we analyzed the tweets content using natural language processing techniques and machine-learning based algorithms, and inferred seventeen latent semantic attributes associated with each tweet, including 1) ten attributes indicating the tweet’s relevance to ten detected topics, 2) five quantitative attributes indicating the degree of intensity in the valence (i.e., unpleasantness/pleasantness) and emotional intensities across four primary emotions of fear, anger, sadness and joy, and 3) two qualitative attributes indicating the sentiment category and the most dominant emotion category, respectively. To illustrate how the dataset can be used, we present descriptive statistics around the topics, sentiments and emotions attributes and their temporal distributions, and discuss possible applications in communication, psychology, public health, economics and epidemiology.

Availability
Download
Relations
  • Is version of
    DOI: 10.3886/E120321
Publications
  • “Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends.” JMIR Public Health Surveill, n.d.

Update Metadata: 2020-07-18 | Issue Number: 1 | Registration Date: 2020-07-18

Yang, Yinping (2020): COVID-19 Twitter Dataset with Latent Topics, Sentiments and Emotions Attributes. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E120321V1