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Bei Yu 0002

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affiliation: Syracuse University, School of Information Studies, Syracuse, NY, USA
affiliation (2006 - 2009): Northwestern University, Evanston, IL, USA
affiliation (PhD 2006): University of Illinois at Urbana-Champaign, Graduate School of Library and Information Science, Urbana, IL, USA

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2020 – today

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2023
[c31]
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Yuheun Kim, Lu Guo, Bei Yu, Yingya Li:
Can ChatGPT Understand Causal Language in Science Claims? WASSA@ACL 2023: 379-389
2022
[c30]
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Yingya Li, Bei Yu:
Advice Giving in Medical Research Literature. iConference (2) 2022: 261-272
2021
[j5]
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Shijie Song, Yan Zhang, Bei Yu:
Interventions to support consumer evaluation of online health information credibility: A scoping review. Int. J. Medical Informatics 145: 104321 (2021)
[c29]
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Yingya Li, Jun Wang, Bei Yu:
Detecting Health Advice in Medical Research Literature. EMNLP (1) 2021: 6018-6029
[c28]
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Jun Wang, Kelly Cui, Bei Yu:
Self Promotion in US Congressional Tweets. NAACL-HLT 2021: 4893-4899
[c27]
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Jun Wang, Bei Yu:
News2PubMed: A Browser Extension for Linking Health News to Medical Literature. SIGIR 2021: 2605-2609
[i1]
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Jun Wang, Bei Yu:
Linking Health News to Research Literature. CoRR abs/2107.06472 (2021)
2020
[c26]
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Bei Yu, Jun Wang, Lu Guo, Yingya Li:
Measuring Correlation-to-Causation Exaggeration in Press Releases. COLING 2020: 4860-4872
[c25]
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Haichen Zhou, Bei Yu:
Information Quality of Reddit Link Posts on Health News. iConference 2020: 186-197

2010 – 2019

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2019
[j4]
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Bei Yu, Xiao Hu:
Toward Training and Assessing Reproducible Data Analysis in Data Science Education. Data Intell. 1(4): 381-392 (2019)
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Shi Yuan, Bei Yu:
HClaimE: A tool for identifying health claims in health news headlines. Inf. Process. Manag. 56(4): 1220-1233 (2019)
[c24]
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Bei Yu, Yingya Li, Jun Wang:
Detecting Causal Language Use in Science Findings. EMNLP/IJCNLP (1) 2019: 4663-4673
[c23]
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Yingya Li, Bei Yu:
Identifying Finding Sentences in Conclusion Subsections of Biomedical Abstracts. iConference 2019: 679-689
2018
[c22]
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Shi Yuan, Bei Yu:
An Evaluation of Information Extraction Tools for Identifying Health Claims in News Headlines. EventStory@Coling 2018: 34-43
[c21]
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Jian Qin, Bei Yu, Liya Wang:
Knowledge Node and Relation Detection. NKOS@TPDL 2018: 29-44
[c20]
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Bei Yu, Yihan Yu:
Auto-Tracking Controversial Topics in Social-Media-Based Customer Dialog: A Case Study on Starbucks. iConference 2018: 87-96
2017
[c19]
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Xiao Hu, Bei Yu, Sue Alman, Allen H. Renear, Toni Carbo:
Teaching information science and technology to the world? Practices, challenges and visions. ASIST 2017: 566-569
[c18]
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Yingya Li, Jieke Zhang, Bei Yu:
An NLP Analysis of Exaggerated Claims in Science News. NLPmJ@EMNLP 2017: 106-111
2016
[c17]
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Ye Chen, Bei Yu, Xuewei Zhang, Yihan Yu:
Topic modeling for evaluating students' reflective writing: a case study of pre-service teachers' journals. LAK 2016: 1-5
[e2]
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Jon Atle Gulla, Bei Yu, Özlem Özgöbek, Nafiseh Shabib:
Proceedings of the 3rd International Workshop on News Recommendation and Analytics (INRA 2015) co-located with 9th ACM Conference on Recommender Systems (RecSys 2015), Vienna, Austria, September 20, 2015. CEUR Workshop Proceedings 1542, CEUR-WS.org 2016 [contents]
2015
[c16]
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Jon Atle Gulla, Bei Yu, Özlem Özgöbek, Nafiseh Shabib:
3rd International Workshop on News Recommendation and Analytics (INRA 2015). RecSys 2015: 345-346
2014
[j2]
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Bei Yu:
Language and gender in Congressional speech. Lit. Linguistic Comput. 29(1): 118-132 (2014)
[c15]
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Bei Yu, Daniele Fanelli:
Classifying Negative Findings in Biomedical Publications. BioNLP@ACL 2014: 19-23
2013
[c14]
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Bei Yu:
Automated citation sentiment analysis: What can we learn from biomedical researchers. ASIST 2013: 1-9
2012
[c13]
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Bei Yu:
Function Words for Chinese Authorship Attribution. CLfL@NAACL-HLT 2012: 45-53
[c12]
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Jun Wang, Bei Yu:
Collecting Representative Pictures for Words: A Human Computation Approach Based on Draw Something Game. HCOMP@AAAI 2012
2011
[c11]
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Bei Yu:
The emotional world of health online communities. iConference 2011: 806-807
[c10]
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Xiao Hu, Bei Yu:
Exploring The Relationship Between Mood and Creativity in Rock Lyrics. ISMIR 2011: 789-794
[c9]
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Bei Yu, Miao Chen, Linchi Kwok:
Toward Predicting Popularity of Social Marketing Messages. SBP 2011: 317-324
2010
[c8]
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Bei Yu, Min-Chun Ku:
Collecting legacy corpora from social science research for text mining evaluation. ASIST 2010: 1-2
[c7]
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Jun Wang, Bei Yu:
Sentence recall game: a novel tool for collecting data to discover language usage patterns. HCOMP@KDD 2010: 56-59

2000 – 2009

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2009
[c6]
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Bei Yu, Maojin Jiang:
TSA'09 workshop summary: topic-sentiment analysis. CIKM 2009: 2115-2116
[e1]
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Maojin Jiang, Bei Yu:
Proceedings of the 1st International CIKM Workshop on Topic-Sentiment Analysis for Mass Opinion, TSA '09, Hong Kong, SAR, China, November 6, 2009. ACM 2009, ISBN 978-1-60558-805-6 [contents]
2008
[j1]
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Bei Yu:
An evaluation of text classification methods for literary study. Lit. Linguistic Comput. 23(3): 327-343 (2008)
[c5]
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Bei Yu, Stefan Kaufmann, Daniel Diermeier:
Exploring the characteristics of opinion expressions for political opinion classification. DG.O 2008: 82-91
[c4]
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Haifeng Shao, Bei Yu, Joseph H. Nadeau:
Strangeness-based feature weighting and classification of gene expression profiles. SAC 2008: 1292-1296
2006
[c3]
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Catherine Plaisant, James Rose, Bei Yu, Loretta Auvil, Matthew G. Kirschenbaum, Martha Nell Smith, Tanya E. Clement, Greg Lord:
Exploring erotics in Emily Dickinson's correspondence with text mining and visual interfaces. JCDL 2006: 141-150
2004
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ChengXiang Zhai, Atulya Velivelli, Bei Yu:
A cross-collection mixture model for comparative text mining. KDD 2004: 743-748
2002
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Jun Wang, Bei Yu, Les Gasser:
Concept Tree Based Clustering Visualization with Shaded Similarity Matrices. ICDM 2002: 697-700

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