SOC-PHCLSIOct 9, 2013

Spatio-temporal variation of conversational utterances on Twitter

arXiv:1310.2479v37 citations
Originality Synthesis-oriented
AI Analysis

This work addresses linguistic change in social media for researchers, but it is incremental as it extends prior findings on utterance shortening to a new dataset.

The study found that conversational utterances on Twitter shortened over three years, with a correlation between shorter utterances and higher percentages of Black population in U.S. states, attributing this to increased jargon usage.

Conversations reflect the existing norms of a language. Previously, we found that utterance lengths in English fictional conversations in books and movies have shortened over a period of 200 years. In this work, we show that this shortening occurs even for a brief period of 3 years (September 2009-December 2012) using 229 million utterances from Twitter. Furthermore, the subset of geographically-tagged tweets from the United States show an inverse proportion between utterance lengths and the state-level percentage of the Black population. We argue that shortening of utterances can be explained by the increasing usage of jargon including coined words.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes