Word Embeddings to Enhance Twitter Gang Member Profile Identification

Preprint English OPEN
Wijeratne, Sanjaya; Balasuriya, Lakshika; Doran, Derek; Sheth, Amit;
  • Subject: Computer Science - Computation and Language | Computer Science - Social and Information Networks | Computer Science - Computers and Society | Computer Science - Information Retrieval

Gang affiliates have joined the masses who use social media to share thoughts and actions publicly. Interestingly, they use this public medium to express recent illegal actions, to intimidate others, and to share outrageous images and statements. Agencies able to uneart... View more
  • References (21)
    21 references, page 1 of 3

    [20007] Survey of Gang Members Online Habits and Participation (2007) Survey results reported at the i-SAFE Annual Internet Safety Education Review Meeting Carlsbad, California. National Assessment Center, 2007.

    2011 National Gang Threat Assessment Issued Emerging Trends. 2011.

    National Gang Report. 2013.

    Y. Bengio, R. Ducharme, P. Vincent, and C. Janvin. A neural probabilistic language model. J. Mach. Learn. Res., 3:1137{1155, March 2003.

    S. Decker and D. Pyrooz. Leaving the gang: Logging o and moving on. council on foreign relations, 2011.

    Y. Hu, K. Talamadupula, and S. Kambhampati. Dude, srsly?: The surprisingly formal nature of twitter's language. In ICWSM, 2013.

    Deep learning. Nature, 521(7553):436{ 444, 2015.

    J. Lilleberg, Y. Zhu, and Y. Zhang. Support vector machines and word2vec for text classi cation with semantic features.

    In Proc. of IEEE ICCI*CC, 2015, pages 136{140, July 2015.

    [20111] [20113] [BDVJ03] [DP11] [HTK13] [LBH15] [LZZ15] [MCCD13] T. Mikolov, K. Chen, G. Corrado, and J. Dean. E cient estimation of word representations in vector space. CoRR, 2013.

  • Related Organizations (1)
  • Metrics
Share - Bookmark