Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
Inferring social ties from common activities in twitter. / Sharma, Umang; Suman, Abhishek; Shannigrahi, Saswata.
HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, 2014. стр. 318-320.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
}
TY - GEN
T1 - Inferring social ties from common activities in twitter
AU - Sharma, Umang
AU - Suman, Abhishek
AU - Shannigrahi, Saswata
PY - 2014/1/1
Y1 - 2014/1/1
N2 - We investigate the extent to which we can infer social ties between a pair of users in an online social network Twitter, based on their common activities defined by the number of common celebrity profiles they are following. In this work, we analyze the list of celebrities that a set of Twitter users are following in December 2013 to infer the social ties that existed between these users till July 2009. We use two probabilistic models given by Kossinets et al. [Science, 2006] and Crandall et al. [PNAS, 2010] for this purpose. The model of Kossinets et al. is meant to give an upper bound for the probability of friendship between a pair of users, whereas the model by Crandall et al. is supposed to give an almost accurate estimate of the same. We observe that the model of Kossinets et al. is able to give an upper bound whereas the model given by Crandall et al. is unable to give an almost accurate estimate for our dataset. However, the model by Crandall et al. is observed to provide a correct estimate of the probability of friendship between the users when we consider following a particular type of celebrity profile, e.g. CEO, Author etc., as the activity of a user.
AB - We investigate the extent to which we can infer social ties between a pair of users in an online social network Twitter, based on their common activities defined by the number of common celebrity profiles they are following. In this work, we analyze the list of celebrities that a set of Twitter users are following in December 2013 to infer the social ties that existed between these users till July 2009. We use two probabilistic models given by Kossinets et al. [Science, 2006] and Crandall et al. [PNAS, 2010] for this purpose. The model of Kossinets et al. is meant to give an upper bound for the probability of friendship between a pair of users, whereas the model by Crandall et al. is supposed to give an almost accurate estimate of the same. We observe that the model of Kossinets et al. is able to give an upper bound whereas the model given by Crandall et al. is unable to give an almost accurate estimate for our dataset. However, the model by Crandall et al. is observed to provide a correct estimate of the probability of friendship between the users when we consider following a particular type of celebrity profile, e.g. CEO, Author etc., as the activity of a user.
KW - inferring social ties
KW - social networks
UR - http://www.scopus.com/inward/record.url?scp=84907393058&partnerID=8YFLogxK
U2 - 10.1145/2631775.2631785
DO - 10.1145/2631775.2631785
M3 - Conference contribution
AN - SCOPUS:84907393058
SN - 9781450329545
SP - 318
EP - 320
BT - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
PB - Association for Computing Machinery
T2 - 25th ACM Conference on Hypertext and Social Media, HT 2014
Y2 - 1 September 2014 through 4 September 2014
ER -
ID: 49849490