IntroductionWelcome to the COLING 2014 Second Workshop on Natural Language Processing for Social Media (SocialNLP). SocialNLP is a new inter-disciplinary area of natural language processing (NLP) and social computing. We consider three plausible directions of SocialNLP: (1) addressing issues in social computing using NLP techniques; (2) solving NLP problems using information from social networks or social media; and (3) handling new problems related to both social computing and natural language processing.Through this workshop, we anticipate to provide a platform for research outcome presentation and head-to-head discussion in the area of SocialNLP, with the hope to combine the insight and experience of prominent researchers from both NLP and social computing domains to contribute to the area of SocialNLP jointly. Also, selected and expanded versions of papers presented at SocialNLP will be published in two follow-on Special Issues of Springer Cognitive Computation (CogComp) and the International Journal of Computational Linguistics and Chinese Language Processing (IJCLCLP).The submissions to this year's workshop were again of high quality and we had a competitive selection process. We received 18 submissions, and due to a rigorous review process, we only accepted 6 of them. Thus the acceptance rate was 33%. We also have 2 invited papers. The workshop papers cover a broad range of SocialNLP-related topics, such as aspect extraction, multi-lingual sentiment analysis, sentiment feature selection, online rating prediction, sentiment sequence recognition, automatic identification, verbal behavior and persuasiveness analysis, and user classification. We had a total of 18 reviewers. We warmly thank our PC members for the timely reviews and constructive comments. AbstractIn ironic texts what is literally said is usually negated, and in absence of an explicit negation marker. This makes social computing quite challenging. Detecting irony is very much important for NLP tasks such as polarity classification, sentiment analysis, opinion mining, or reputation analysis. There is a growing interest from the research community in investigating the impact of irony on polarity classification and sentiment analysis. A tasks will be organised at SemEval in 2015 on Sentiment Analysis of Figurative Language in Twitter (http://alt.qcri.org/semeval2015/task11). What are the linguistic patterns that users employ in social media in order to try to be ironic in just maybe 140 characters? Linguistic devices that go beyond positive or negative polarity such as ambiguity, incongruity, unexpectedness and emotional contexts have an important role as triggers of irony. In the talk I will describe how irony is employed in social media texts (Twitter, Amazon, Facebook etc.) and what are the recent stateof-the-art attempts for its automatic detection. At the end of the talk, I will address also the even more challenging and fine-grained problem of distinguishing among irony, sarcasm and satire: e.g. If you find it hard to laugh at yourself, I...
ii SocialNLP@EACL2017 Chairs' Welcome It is our great pleasure to welcome you to the Fifth International Workshop on Natural Language Processing for SocialMedia-SocialNLP 2017, associated with EACL 2017. SocialNLP is an interdisciplinary area of natural language processing (NLP) and social computing. We hold SocialNLP twice a year: one in the NLP venue, the other in the associated venue such as those for web technology or artificial intelligence. There are three plausible directions of SocialNLP: (1) addressing issues in social computing using NLP techniques; (2) solving NLP problems using information from social media; and (3) handling new problems related to both social computing and natural language processing. Through this workshop, we anticipate to provide a platform for research outcome presentation and head-to-head discussion in the area of SocialNLP, with the hope to combine the insight and experience of prominent researchers from both NLP and social computing domains to contribute to the area of SocialNLP jointly. The submissions to this year's workshop were again of high quality and we had a competitive selection process. We received 13 submissions from Asia, Europe, and the United States, and due to a rigorous review process, we only accepted 6 long oral papers. Thus the acceptance rate was 46 percent. Compared to the recent workshops in United States, the submission number is a bit small. This also encourages us to have more related activities in Europe to expand our community here.This year, we are delighted to have Prof. Dirk Hovy, from the University of Copenhagen, as our keynote speaker. We also encourage attendees to attend the keynote and invited talk presentation to have more discussions with outstanding researchers. Their valuable and insightful talk can and will guide us to a better understanding of the future. Putting together SocialNLP 2017 was a team effort. We first thank the authors for providing the quality content of the program. We are grateful to the program committee members, who worked very hard in reviewing papers and providing feedback for authors. Finally, we especially thank the Workshop Committee Chairs Prof. Laura Rimell and Prof. Richard Johansson.We hope you join our community and enjoy the workshop! OrganizersLun-Wei Ku, Academia Sincia, Taiwan Cheng-Te Li, National Cheng Kung University, Taiwan AbstractThis paper presents a survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing. Due to the massive scale of the web, methods that automatically detect hate speech are required. Our survey describes key areas that have been explored to automatically recognize these types of utterances using natural language processing. We also discuss limits of those approaches.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.