Interdisciplinarity

“Twitterology: a new science?”

November 10, 2011 2368

Ben Zimmer writes in the New York Times about Twitter’s appeal to social scientists who are looking for real-time language data and social interactions to analyze. He writes: “Twitter’s appeal to researchers is its immediacy – and its immensity. Instead of relying on questionnaires and other laborious and time-consuming methods of data collection, social scientists can simply take advantage of Twitter’s stream to eavesdrop on a virtually limitless array of language in action.”

Examples of how Twitter has been used by researchers include tracking on-the-ground sentiment in Egypt and Libya over the course of the Arab Spring, looking at how emotions may relate to the rhythms of daily life, and building maps of regional language use across the United States.

Read the full article here.

Related Articles

From ‘Which Database?’ to ‘Under What Conditions?’: Teaching Critical Thinking Through Search Tool Selection in an AI Age
Critical Thinking
April 28, 2026

From ‘Which Database?’ to ‘Under What Conditions?’: Teaching Critical Thinking Through Search Tool Selection in an AI Age

Read Now
Celebrating Arab American Heritage Month
Interdisciplinarity
April 13, 2026

Celebrating Arab American Heritage Month

Read Now
Celebrating the National Survey of Health and Development: 1946-2026
Research
March 9, 2026

Celebrating the National Survey of Health and Development: 1946-2026

Read Now
Why is It So Difficult to Agree About Masks and Respiratory Infections?
Public Policy
January 9, 2026

Why is It So Difficult to Agree About Masks and Respiratory Infections?

Read Now
Critical Thinking is Critical in Universities

Critical Thinking is Critical in Universities

In an age of homogeneous thinking, where peers, AI or a favorite social media personality or politician present perspectives as facts, it […]

Read Now
A Psychologist Explains Replication (and Why It’s Not the Same as Reproducibility)

A Psychologist Explains Replication (and Why It’s Not the Same as Reproducibility)

Back in high school chemistry, I remember waiting with my bench partner for crystals to form on our stick in the cup […]

Read Now
A Look at How Large Language Models  Transform Research

A Look at How Large Language Models Transform Research

Generative AI, especially large language models (LLMs), present exciting and unprecedented opportunities and complex challenges for academic research and scholarship. As the […]

Read Now
0 0 votes
Article Rating
Subscribe
Notify of
guest

This site uses Akismet to reduce spam. Learn how your comment data is processed.

1 Comment
Newest
Oldest Most Voted
Inline Feedbacks
View all comments
@empsocsci

Social scientists/humanities scholars should treat this idea with caution. The degree of algorithmic (or even intentional) pre-filtering of twitter’s various API feeds is unclear, tweeters are clearly a non-representative (& non-random) sample who are self-selecting a) as users/tweeters and b) as those who choose to make tweets public and even c) those who choose to allow geo-coding of tweets if that’s your analytic interest. Response bias is therefore unclear and potentially unknowable. Generalisability of results is therefore dubious. I’d encourage anyone thinking about using these and related kinds of data to consider @katecrawford and @zephoria’s Six Provocations for Big Data… Read more »