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AttitudeBuzz
2015
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15
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We apply AttitudeBuzz to the domain of homophobic attitudes expressed on Twitter. The resulting user interface is presented and the machine learning model described and analyzed. ...
AttitudeBuzz is a system that analyzes and presents complex social attitudes based on geolocated social media data. ...
as one inspiration for our research. This work was supported in part by the John S. and James L. Knight Foundation, the National Science Foundation (under grant IIS-0917261), and Google. ...
doi:10.1145/2808797.2809336
dblp:conf/asunam/CohnKB15
fatcat:xexu7s5kxnhkxatz7kpyteaflq
Network vs Market Relations
2015
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15
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2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
[6] P. ...
ASONAM '15, August 25-28, 2015, Paris, France 226
© 2015 ACM. ...
doi:10.1145/2808797.2808904
dblp:conf/asunam/HorvatUU15
fatcat:sgqk7o6vvbedheual6hgmqw44u
Event Detection
2015
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15
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public transport network-to demonstrate the promise of our approaches: the addition of group and socio-physical tie-strength based features increases recall (the percentage of events detected) more than ...
This paper investigates how digital traces of people's movements and activities in the physical world (e.g., at college campuses and commutes) may be used to detect local, short-lived events in various ...
ACKNOWLEDGMENTS ASONAM '15, August 25-28, 2015, Paris, France. Copyright c 2015 ACM. ...
doi:10.1145/2808797.2809387
dblp:conf/asunam/JayarajahMRL15
fatcat:ewjpdos6jbgihl7mtwpp5g3o34
Real-time Classification of Malicious URLs on Twitter using Machine Activity Data
2015
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15
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ASONAM '15, August 25-28, 2015, Paris, France ACM ISBN 978-1-4503-3854-7/15/08 ...
Massive online social networks with hundreds of millions of active users are increasingly being used by Cyber criminals to spread malicious software (malware) to exploit vulnerabilities on the machines ...
ACKNOWLEDGMENT This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Global Uncertainties Consortia for Exploratory Research in Security (CEReS) programme, grant number ...
doi:10.1145/2808797.2809281
dblp:conf/asunam/BurnapJRA15
fatcat:73n3pebjtva7jastqvsskteili
User modeling for point-of-interest recommendations in location-based social networks: the state-of-the-art
[article]
2017
arXiv
pre-print
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Location-based social networks(LBSNs)allow users to check-in at a physical location and share daily tips on points-of-interest (POIs) with their friends anytime and anywhere. ...
This paper focuses on reviewing the taxonomy of user modeling for POI recommendations through the data analysis of LBSNs. ...
Acknowledgements This work is supported by National Scien ce Foundation of China (NO. 61602518) and Open Foundation of Hubei Key Laboratory of Intelligent Geo-Information Processing (No.K ...
arXiv:1712.06768v1
fatcat:nzmsjj6kjzby7ldi3czf6zlkye
Internet of Things (IoT) Implementation in Learning Institutions: A Systematic Literature Review
2021
Pertanika journal of science & technology
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The outcomes revealed that the utilization of IoT for tracking and tracing a learner's attendance had been one of the application areas of IoT in education. ...
Millennial learners, growth in enrolment numbers in universities, and the need for equity and quality learning necessitate the use of IoT technologies in education. ...
In 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 1032-1035). ...
doi:10.47836/pjst.29.1.26
fatcat:7o42ndcuarbnvam4wc7x5ltoqm
Mapping (Dis-)Information Flow about the MH17 Plane Crash
2019
Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom: Censorship, Disinformation, and Propaganda
unpublished
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A total of 39 teams submitted runs; 21 teams participated in the FLC subtask and 35 teams took part in the SLC subtask. ...
We further featured a shared task on the identification of propaganda in news articles. The task included two subtasks with different levels of complexity. ...
Acknowledgements We would like to thank Dr Leandro Minku from the University of Birmingham for his insights into and help with the statistical analysis presented in this paper. ...
doi:10.18653/v1/d19-5006
fatcat:77l3dndrkvfmlhjt6qvnrassgi