28 citations · 39 across the 4 of their papers we have counts for
6 papers
A Sentiment Analysis of Breast Cancer Treatment Experiences and Healthcare Perceptions Across Twitter
Eric M. Clark, Ted James, Chris A. Jones +4
Background: Social media has the capacity to afford the healthcare industry with valuable feedback from patients who reveal and express their medical decision-making process, as we…
Vaporous Marketing: Uncovering Pervasive Electronic Cigarette Advertisements on Twitter
Eric M. Clark, Chris A. Jones, Jake Ryland Williams +4
Background: Twitter has become the "wild-west" of marketing and promotional strategies for advertisement agencies. Electronic cigarettes have been heavily marketed across Twitter f…
Reply to Garcia et al.: Common mistakes in measuring frequency dependent word characteristics
P. S. Dodds, E. M. Clark, S. Desu +11
We demonstrate that the concerns expressed by Garcia et al. are misplaced, due to (1) a misreading of our findings in [1]; (2) a widespread failure to examine and present words in…
Sifting Robotic from Organic Text: A Natural Language Approach for Detecting Automation on Twitter
Eric M. Clark, Jake Ryland Williams, Chris A. Jones +3
Twitter, a popular social media outlet, has evolved into a vast source of linguistic data, rich with opinion, sentiment, and discussion. Due to the increasing popularity of Twitter…
Human language reveals a universal positivity bias
Peter Sheridan Dodds, Eric M. Clark, Suma Desu +11
Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language…
Zipf's law holds for phrases, not words
Jake Ryland Williams, Paul R. Lessard, Suma Desu +4
With Zipf's law being originally and most famously observed for word frequency, it is surprisingly limited in its applicability to human language, holding over no more than three t…