Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Roy, Deb"'
Autor:
Fulay, Suyash, Roy, Deb
While political polarization has increased as measured through surveys, currently we lack comprehensive, longitudinal, and ecologically valid measurement of the polarization of online political speech that spans social media platforms. Using language
Externí odkaz:
http://arxiv.org/abs/2308.15556
Identity spans multiple dimensions; however, the relative salience of a dimension of identity can vary markedly from person to person. Furthermore, there is often a difference between one's internal identity (how salient different aspects of one's id
Externí odkaz:
http://arxiv.org/abs/2304.07195
As political attitudes have diverged ideologically in the United States, political speech has diverged lingusitically. The ever-widening polarization between the US political parties is accelerated by an erosion of mutual understanding between them.
Externí odkaz:
http://arxiv.org/abs/2209.07065
We study how political polarization is reflected in the social media posts used by media outlets to promote their content online. In particular, we track the Twitter posts of several media outlets over the course of more than three years (566K tweets
Externí odkaz:
http://arxiv.org/abs/2111.02646
The intensification of affective polarization worldwide has raised new questions about how social media platforms might be further fracturing an already-divided public sphere. As opposed to ideological polarization, affective polarization is defined
Externí odkaz:
http://arxiv.org/abs/2110.05596
Social media platforms promise to enable rich and vibrant conversations online; however, their potential is often hindered by antisocial behaviors. In this paper, we study the relationship between structure and toxicity in conversations on Twitter. W
Externí odkaz:
http://arxiv.org/abs/2105.11596
Homophily -- our tendency to surround ourselves with others who share our perspectives and opinions about the world -- is both a part of human nature and an organizing principle underpinning many of our digital social networks. However, when it comes
Externí odkaz:
http://arxiv.org/abs/1803.01731
We present Tweet2Vec, a novel method for generating general-purpose vector representation of tweets. The model learns tweet embeddings using character-level CNN-LSTM encoder-decoder. We trained our model on 3 million, randomly selected English-langua
Externí odkaz:
http://arxiv.org/abs/1607.07514
This paper describes our approach for the Detecting Stance in Tweets task (SemEval-2016 Task 6). We utilized recent advances in short text categorization using deep learning to create word-level and character-level models. The choice between word-lev
Externí odkaz:
http://arxiv.org/abs/1606.05694
There is an ever growing number of users with accounts on multiple social media and networking sites. Consequently, there is increasing interest in matching user accounts and profiles across different social networks in order to create aggregate prof
Externí odkaz:
http://arxiv.org/abs/1605.05166