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SocialNLP@WWW 2018 Chairs' Welcome & Organization

Published: 23 April 2018 Publication History

Abstract

With the rapid growing of social networking services (e.g., Facebook and Twitter), being able to process data come from such platforms has gained much attention in recent years. SocialNLP is a new inter-disciplinary area of natural language processing (NLP) and social computing. 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. Several challenges are foreseeable in SocialNLP. First, the message lengths on social media are usu-ally short, and thus it is difficult to apply traditional NLP approaches directly. Second, social media contains heterogeneous information (e.g. tags, friends, followers, likes, and retweets) that should be considered together with the contents for better quality of analysis. Finally, social media contents always involve multiple persons with slangs and jargons, and usually require special techniques to process. We organize SocialNLP in WWW 2018 with three goals. First, social media data is essentially generated and collected from online social services that are functioned based on Web techniques. One can leverage Web techniques to investigate various user behaviors and investigate the interactions between users. Second, user-generated data in social media is mainly in the form of text. Theories and techniques on Web information retrieval and natural language processing are desired for semantic understanding, accurate search, and efficient processing of big social media data. Third, from the perspective of application, if social media data can be effectively processed to distill the collective knowledge of users, novel Web applications, such as emergency management, social recommendation, and future prediction, can be developed with higher accuracy and better user experience. We expect SocialNLP workshop in WWW community can provide mutually-reinforced benefits for researchers in areas of Web techniques, information retrieval and social media analytics.

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    cover image ACM Other conferences
    WWW '18: Companion Proceedings of the The Web Conference 2018
    April 2018
    2023 pages
    ISBN:9781450356404
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • IW3C2: International World Wide Web Conference Committee

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    International World Wide Web Conferences Steering Committee

    Republic and Canton of Geneva, Switzerland

    Publication History

    Published: 23 April 2018

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    Author Tags

    1. natural language processing
    2. sentiment analysis
    3. social media
    4. text mining

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    • Introduction

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    WWW '18
    Sponsor:
    • IW3C2
    WWW '18: The Web Conference 2018
    April 23 - 27, 2018
    Lyon, France

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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