English

Analyzing Temporal Relationships between Trending Terms on Twitter and Urban Dictionary Activity

Computation and Language 2020-05-19 v2 Social and Information Networks

Abstract

As an online, crowd-sourced, open English-language slang dictionary, the Urban Dictionary platform contains a wealth of opinions, jokes, and definitions of terms, phrases, acronyms, and more. However, it is unclear exactly how activity on this platform relates to larger conversations happening elsewhere on the web, such as discussions on larger, more popular social media platforms. In this research, we study the temporal activity trends on Urban Dictionary and provide the first analysis of how this activity relates to content being discussed on a major social network: Twitter. By collecting the whole of Urban Dictionary, as well as a large sample of tweets over seven years, we explore the connections between the words and phrases that are defined and searched for on Urban Dictionary and the content that is talked about on Twitter. Through a series of cross-correlation calculations, we identify cases in which Urban Dictionary activity closely reflects the larger conversation happening on Twitter. Then, we analyze the types of terms that have a stronger connection to discussions on Twitter, finding that Urban Dictionary activity that is positively correlated with Twitter is centered around terms related to memes, popular public figures, and offline events. Finally, We explore the relationship between periods of time when terms are trending on Twitter and the corresponding activity on Urban Dictionary, revealing that new definitions are more likely to be added to Urban Dictionary for terms that are currently trending on Twitter.

Keywords

Cite

@article{arxiv.2005.07655,
  title  = {Analyzing Temporal Relationships between Trending Terms on Twitter and Urban Dictionary Activity},
  author = {Steven R. Wilson and Walid Magdy and Barbara McGillivray and Gareth Tyson},
  journal= {arXiv preprint arXiv:2005.07655},
  year   = {2020}
}

Comments

Accepted at The Web Science Conference 2020

R2 v1 2026-06-23T15:34:40.761Z