Temporal semantic centrality for the analysis of communication networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7387 LNCS, Issue , 2012, Pages 177-184

  Leprovost, Damien ^a   Abrouk, Lylia ^a   Cullot, Nadine ^a   Gross Amblard, David ^b  

^a UNIVERSITÉ DE BOURGOGNE   (France)

^b UNIVERSITÉ DE RENNES 1   (France)

Author keywords

centrality; communication network; community; ontology; semantic analysis

Indexed keywords

CENTRALITY; COMMUNICATION STRUCTURES; COMMUNITY; DATA SETS; EFFICIENT IMPLEMENTATION; MESSAGE SEMANTICS; ONLINE COMMUNITIES; SEMANTIC ANALYSIS; SEMANTIC PROPAGATION;

ONTOLOGY; TELECOMMUNICATION NETWORKS;

SEMANTICS;

EID: 84865126701     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-31753-8_13     Document Type: Conference Paper

References (12)

1. Java, A., Song, X., Finin, T., Tseng, B.: Why we twitter: understanding microblogging usage and communities. In: Proceedings of the 9th Workshop on Web Mining and Social Network Analysis (WebKDD), pp. 56-65. ACM (2007)
2. Sankaranarayanan, J., Samet, H., Teitler, B., Lieberman, M., Sperling, J.: Twitterstand: news in tweets. In: Proceedings of the 17th International Conference on Advances in Geographic Information Systems (SIGSPATIAL), pp. 42-51. ACM (2009)
3. Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes Twitter users: real-time event detection by social sensors. In: Proceedings of the 19th International Conference on World Wide Web (WWW), pp. 851-860. ACM (2010)
4. Benson, E., Haghighi, A., Barzilay, R.: Event discovery in social media feeds. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL-HLT 2011), pp. 389-398. Association for Computational Linguistics (2011)
5. Abel, F., Celik, I., Houben, G.-J., Siehndel, P.: Leveraging the Semantics of Tweets for Adaptive Faceted Search on Twitter. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 1-17. Springer, Heidelberg (2011)
6. Becker, H., Chen, F., Iter, D., Naaman, M., Gravano, L.: Automatic identification and presentation of twitter content for planned events. In: Proceedings of the 5th International AAAI Conference on Weblogs and Social Media (ICWSM 2011), pp. 655-656. AAAI Press (2011)
7. Popescu, A., Pennacchiotti, M., Paranjpe, D.: Extracting events and event descriptions from Twitter. In: Proceedings of the 20th International Conference on World Wide Web (WWW), pp. 105-106. ACM (2011)
8. Becker, H., Naaman, M., Gravano, L.: Beyond trending topics: Real-world event identification on twitter. In: Proceedings of the 5th International AAAI Conference on Weblogs and Social Media (ICWSM), North America, pp. 438-441. AAAI Press (July 2011)
9. Chakrabarti, D., Punera, K.: Event summarization using tweets. In: Proceedings of the 5th International Conference on Weblogs and Social Media (ICWSM), pp. 66-73. AAAI Press (2011)
10. Lewis, D.: Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398, pp. 4-15. Springer, Heidelberg (1998)
11. Kanaris, I., Kanaris, K., Houvardas, I., Stamatatos, E.: Words vs. character n-grams for anti-spam filtering. International Journal on Artificial Intelligence Tools 16(6), 1047-1067 (2007)
12. Hovold, J.: Naive bayes spam filtering using word-position-based attributes. In: Proceedings of the Second Conference on Email and Anti-Spam (CEAS 2005), Stanford University, California, USA, pp. 1-8 (2005)