📰 International Workshop on Natural Language Processing for Social Media 2016 — accepted papers

International Workshop on Natural Language Processing for Social Media 2016 is the 2016 edition of the International Workshop on Natural Language Processing for Social Media, held in Austin, TX, USA, November 2016 (publisher: Association for Computational Linguistics). OpenAlex lists 13 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. emoji2vec: Learning Emoji Representations from their DescriptionBen Eisner, Tim Rocktäschel, Isabelle Augenstein et al.291 citations · our summary
2. Identifying and Categorizing Disaster-Related TweetsKevin Stowe, Michael J. Paul, Martha Palmer et al.82 citations
3. Hierarchical Character-Word Models for Language IdentificationAaron Jaech, George Mulcaire, Shobhit Hathi et al.41 citations
4. Identifying Eyewitness News-worthy Events on TwitterErika Doggett, Alejandro Cantarero21 citations
5. Why Do They Leave: Modeling Participation in Online Depression ForumsFarig Sadeque, Ted Pedersen, Thamar Solorio et al.18 citations
6. Twitter at the Grammys: A Social Media Corpus for Entity Linking and DisambiguationMark Dredze, Nicholas Andrews, Jay DeYoung16 citations
7. Witness Identification in TwitterRui Fang, Armineh Nourbakhsh, Xiaomo Liu et al.16 citations
8. Learning Latent Local Conversation Modes for Predicting Comment Endorsement in Online DiscussionsHao Fang, Hao Cheng, Mari Ostendorf12 citations
9. Detecting Social Roles in TwitterSunghwan Mac Kim, Stephen Wan, Cécile Paris9 citations
10. Human versus Machine Attention in Document Classification: A Dataset with Crowdsourced AnnotationsNikolaos Pappas, Andrei Popescu-Belis7 citations

All accepted papers (13)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. emoji2vec: Learning Emoji Representations from their DescriptionBen Eisner, Tim Rocktäschel, Isabelle Augenstein et al.291 citations · our summary
2. Identifying and Categorizing Disaster-Related TweetsKevin Stowe, Michael J. Paul, Martha Palmer et al.82 citations
3. Hierarchical Character-Word Models for Language IdentificationAaron Jaech, George Mulcaire, Shobhit Hathi et al.41 citations
4. Identifying Eyewitness News-worthy Events on TwitterErika Doggett, Alejandro Cantarero21 citations
5. Why Do They Leave: Modeling Participation in Online Depression ForumsFarig Sadeque, Ted Pedersen, Thamar Solorio et al.18 citations
6. Twitter at the Grammys: A Social Media Corpus for Entity Linking and DisambiguationMark Dredze, Nicholas Andrews, Jay DeYoung16 citations
7. Witness Identification in TwitterRui Fang, Armineh Nourbakhsh, Xiaomo Liu et al.16 citations
8. Learning Latent Local Conversation Modes for Predicting Comment Endorsement in Online DiscussionsHao Fang, Hao Cheng, Mari Ostendorf12 citations
9. Detecting Social Roles in TwitterSunghwan Mac Kim, Stephen Wan, Cécile Paris9 citations
10. Human versus Machine Attention in Document Classification: A Dataset with Crowdsourced AnnotationsNikolaos Pappas, Andrei Popescu-Belis7 citations
11. Steps Toward Automatic Understanding of the Function of Affective Language in Support GroupsAmit Navindgi, Caroline Brun, Cécile Boulard Masson et al.6 citations
12. How Do I Look? Publicity Mining From Distributed Keyword Representation of Socially Infused News ArticlesYu-Lun Hsieh, Yung-Chun Chang, Chun-Han Chu et al.4 citations
13. Identifying Sensible Participants in Online DiscussionsSiddharth Jain1 citation

📄 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. emoji2vec: Learning Emoji Representations from their DescriptionBen Eisner, Tim Rocktäschel, Isabelle Augenstein, et al.2016 · 360 citations

📚 Fields

🎭Arts and Humanities (1)🖥️Computer Science (1)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/venues/socialnlp/2016/