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Haters gonna hate: job-related offenses in twitter

Published: 07 April 2014 Publication History

Abstract

In this paper, we aim at finding out which users are likely to publicly demonstrate frustration towards their jobs on the microblogging platform Twitter - we will call these users haters. We show that the profiles of haters have specific characteristics in terms of vocabulary and connections. The implications of these findings may be used for the development of an early alert system that can help users to think twice before they post potentially self-harming content.

References

[1]
A. Go, R. Bhayani, and L. Huang. Twitter sentiment classification using distant supervision. Technical report, Stanford.
[2]
R. Kawase, B. P. Nunes, E. Herder, W. Nejdl, and M. A. Casanova. Who wants to get fired? In WebSci, pages 191--194, 2013.
[3]
M. Madden. Privacy management on social media sites. Technical report, Pew Internet and American Life Project, 2012.

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    WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web
    April 2014
    1396 pages
    ISBN:9781450327459
    DOI:10.1145/2567948

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    • IW3C2: International World Wide Web Conference Committee

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    Association for Computing Machinery

    New York, NY, United States

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    Published: 07 April 2014

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    Author Tags

    1. fireme!
    2. privacy awareness
    3. social networks
    4. twitter
    5. user issues
    6. webscience

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    WWW '14
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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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