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19942026
most citedThumbs up? Sentiment Classification using Machine Learning Techniques

2.2k citations · 5.7k across the 55 of their papers we have counts for

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8 papers · 1 filter

cs.SI2017★ 17 cited

Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularity

Jack Hessel, Lillian Lee, David Mimno

The content of today's social media is becoming more and more rich, increasingly mixing text, images, videos, and audio. It is an intriguing research question to model the interpla…

cs.SI2016★ 14 cited

Science, AskScience, and BadScience: On the Coexistence of Highly Related Communities

Jack Hessel, Chenhao Tan, Lillian Lee

When large social-media platforms allow users to easily form and self-organize into interest groups, highly related communities can arise. For example, the Reddit site hosts not ju…

cs.SI2016★ 6 cited

Talk it up or play it down? (Un)expected correlations between (de-)emphasis and recurrence of discussion points in consequential U.S. economic policy meetings

Chenhao Tan, Lillian Lee

In meetings where important decisions get made, what items receive more attention may influence the outcome. We examine how different types of rhetorical (de-)emphasis -- including…

cs.SI2016★ 183 cited

Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions

Chenhao Tan, Vlad Niculae, Cristian Danescu-Niculescu-Mizil +1

Changing someone's opinion is arguably one of the most important challenges of social interaction. The underlying process proves difficult to study: it is hard to know how someone'…

cs.SI2015★ 59 cited

All Who Wander: On the Prevalence and Characteristics of Multi-community Engagement

Chenhao Tan, Lillian Lee

Although analyzing user behavior within individual communities is an active and rich research domain, people usually interact with multiple communities both on- and off-line. How d…

cs.SI2014★ 49 cited

The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter

Chenhao Tan, Lillian Lee, Bo Pang

Consider a person trying to spread an important message on a social network. He/she can spend hours trying to craft the message. Does it actually matter? While there has been exten…