Paper Info
Title
Analyzing Temporal Relationships between Trending Terms on Twitter and Urban Dictionary Activity
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.
Year
DOI
Venue
2020
10.1145/3394231.3397905
WebSci '20: 12th ACM Conference on Web Science Southampton United Kingdom July, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-7989-2
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Steven R. Wilson1127.21
Walid Magdy252040.47
Barbara McGillivray376.22
Gareth Tyson444346.65