Dealing with big data: The case of Twitter

Computational Linguistics in the Netherlands Journal

Volumn 3, Issue , 2013, Pages 121-134

  Sang, Erik Tjong Kim ^a   Van Den Bosch, Antal ^b  

^a NETHERLANDS ESCIENCE CENTER   (Netherlands)

^b RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

BIG DATA; COMPUTATIONAL LINGUISTICS; DIGITAL STORAGE; PARALLEL ARCHITECTURES; SOCIAL NETWORKING (ONLINE);

DATA PROBLEMS; HADOOP FRAMEWORKS; PARALLEL COMPUTING ARCHITECTURE; SOCIAL MEDIA; SOCIAL MEDIA DATUM; STRUCTURED TEXT; VERY LARGE DATUM; WORD FREQUENCIES;

DATA HANDLING;

EID: 84907939355     PISSN: 22114009     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. Church, Kenneth, William Gale, Patrick Hanks, and Donald Hindle (1991), Using statistics in lexical analysis, in Zernik, Uri, editor, Lexical Acquisition: Exploiting On-Line Resources to Build a Lexicon, Lawrence Erlbaum Associates.
2. Gupta, Pankaj, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Zadeh (2013), WTF: the Who To Follow service at Twitter, Proceedings of the 22th International World Wide Web Conference (WWW 2013), Rio de Janeiro, Brazil, pp. 505-514.
3. Kunneman, Florian A., Ali Hürriyetoglu, and Antal Van Den Bosch (2013), Supporting open-domain event prediction by using cross-domain Twitter messages, Talk presented at Computational Linguistics in The Netherlands (CLIN-2013).
4. Liebrecht, Christine, Florian Kunneman, and Antalvan Den Bosch (2013), The perfect solution for detecting sarcasm in tweets not, Proceedings of the 4th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Association for Computational Linguistics, Atlanta, Georgia, pp. 29-37.
5. Liu, Xiaohua, Shaodian Zhang, Furu Wei, and Ming Zhou (2011), Recognizing named entities in tweets, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, Portland, Oregon, pp. 359-367.
6. Petrović, Sasa, Miles Osborne, and Victor Lavrenko (2010), The Edinburgh Twitter Corpus, Computational Linguistics in a World of Social Media.
7. Tjong Kim Sang, Erik (2011), Het gebruik van Twitter voor taalkundig onderzoek, TABU: Bulletin voor Taalwetenschap 39(1/2), pp. 62-72. (in Dutch).
8. Tumasjan, Andranik, Timm Sprenger, Philipp Sandner, and Isabell Welpe (2010), Predicting elections with Twitter: What 140 characters reveal about political sentiment, Proceedings of the Fourth AAAI conference on Weblogs and Social Media, pp. 178-185.
9. Twitter Inc. (2013), Developer Rules of the Road, https://dev. twitter.com/terms/api-terms (retrieved May 2013).
10. Van Halteren, Hans and Maarten Op De Weegh (2013), Clues for autism in Dutch tweet production, Talk presented at Computational Linguistics in The Netherlands (CLIN-2013).
11. Van Wijngaarden, C., C. R. Verschoor, and C. Bonenkamp (2013), Classifying home locations of Twitter users, Technical report for the course Advanced Information Retrieval, University of Amsterdam.