A Hands-On Guide to Conducting Psychological Research on Twitter
Bibliographic Data
| ID | 21209386 |
|---|---|
| Authors | Sean C Murphy (0000-0002-6783-9906, The University of Melbourne, corresponding author) |
| Year | 2017 |
| Volume | 8 |
| Issue | 4 |
| Pages | 396-412 |
| Publication date | 2017-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Psychological and Personality Science (JOURNAL) |
| Journal identifiers | ISSN: 1948-5506 • E-ISSN: 1948-5514 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/1948550617697178 |
| OpenAlex | W2626289531 |
| Language | EN |
| Citations received | 8 |
| References cited | 20 |
The rising popularity of social media has created valuable opportunities for researchers to quickly and cheaply tap large amounts of data on naturalistic social interactions. One of the most useful and accessible sources of social media data is Twitter. Although Twitter data are free to access, however, the programming tools required to collect and analyze these data are likely to create a barrier for many psychologists. The goal of this article is to reduce that barrier by explaining what data are available from Twitter and providing code and step-by-step instructions to retrieve them. I also review approaches to deriving psychological insight from these data, the accompanying challenges, and potential solutions, providing code to make these tasks easier. Particularly for researchers without access to large participant pools, overseas collaborators, or online panels, Twitter can be an important source of psychological insight
Data science · Internet privacy · Naturalistic observation · Popularity · Psychological research · Social media · World Wide Web · Complex Network Analysis Techniques · Computer Science · Media Influence and Health · Mental Health via Writing · Psychology · Social Psychology
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| Citations per year | 0.89 |
|---|---|
| Citation span | 2017 - 2023 (7) |
| Highly cited | No |