Microblogging services like Twitter have witnessed a flood of users and short updates (tweets). Although this phenomenon brings new possibilities of communication, it also brings dangerous consequences. From time to time, people post tweets guided by strong emotions. By default, tweets are public and anyone, anywhere can instantly see your updates, creating high exposure and lack of awareness about privacy issues. In many cases, this may lead to consequences that can be harmful to one's personal and professional life. In this paper, we investigate the posting behavior of people who tweet that they hate their jobs and bosses and their responses to alerts about the potential damage that such a tweet may cause. We show that, in many cases, people are not aware about the dimension of their audience, and once alerted, they often regret what they have publicly said. Our analysis leads us to believe that many users could benefit from a 'give a second thought before posting' tool that may save their jobs.
%0 Conference Paper
%1 kawase2013wants
%A Kawase, Ricardo
%A Nunes, Bernardo Pereira
%A Herder, Eelco
%A Nejdl, Wolfgang
%A Casanova, Marco Antonio
%B Proceedings of the 5th Annual ACM Web Science Conference
%C New York, NY, USA
%D 2013
%I ACM
%K 2013 fireme l3s media social twitter
%P 191--194
%R 10.1145/2464464.2464476
%T Who wants to get fired?
%U http://doi.acm.org/10.1145/2464464.2464476
%X Microblogging services like Twitter have witnessed a flood of users and short updates (tweets). Although this phenomenon brings new possibilities of communication, it also brings dangerous consequences. From time to time, people post tweets guided by strong emotions. By default, tweets are public and anyone, anywhere can instantly see your updates, creating high exposure and lack of awareness about privacy issues. In many cases, this may lead to consequences that can be harmful to one's personal and professional life. In this paper, we investigate the posting behavior of people who tweet that they hate their jobs and bosses and their responses to alerts about the potential damage that such a tweet may cause. We show that, in many cases, people are not aware about the dimension of their audience, and once alerted, they often regret what they have publicly said. Our analysis leads us to believe that many users could benefit from a 'give a second thought before posting' tool that may save their jobs.
%@ 978-1-4503-1889-1
@inproceedings{kawase2013wants,
abstract = {Microblogging services like Twitter have witnessed a flood of users and short updates (tweets). Although this phenomenon brings new possibilities of communication, it also brings dangerous consequences. From time to time, people post tweets guided by strong emotions. By default, tweets are public and anyone, anywhere can instantly see your updates, creating high exposure and lack of awareness about privacy issues. In many cases, this may lead to consequences that can be harmful to one's personal and professional life. In this paper, we investigate the posting behavior of people who tweet that they hate their jobs and bosses and their responses to alerts about the potential damage that such a tweet may cause. We show that, in many cases, people are not aware about the dimension of their audience, and once alerted, they often regret what they have publicly said. Our analysis leads us to believe that many users could benefit from a 'give a second thought before posting' tool that may save their jobs.},
acmid = {2464476},
added-at = {2013-08-30T12:42:11.000+0200},
address = {New York, NY, USA},
author = {Kawase, Ricardo and Nunes, Bernardo Pereira and Herder, Eelco and Nejdl, Wolfgang and Casanova, Marco Antonio},
biburl = {https://www.bibsonomy.org/bibtex/255d93cb46335bd7b651cc8bbd1fde89b/jaeschke},
booktitle = {Proceedings of the 5th Annual ACM Web Science Conference},
doi = {10.1145/2464464.2464476},
interhash = {535db8d6076a79818192088c7a190db5},
intrahash = {55d93cb46335bd7b651cc8bbd1fde89b},
isbn = {978-1-4503-1889-1},
keywords = {2013 fireme l3s media social twitter},
location = {Paris, France},
numpages = {4},
pages = {191--194},
publisher = {ACM},
series = {WebSci '13},
timestamp = {2014-07-28T15:57:31.000+0200},
title = {Who wants to get fired?},
url = {http://doi.acm.org/10.1145/2464464.2464476},
year = 2013
}