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Co-occurrence prediction in a large location-based social network
2013
Frontiers of Computer Science
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Then we propose a machine learning formula for predicting co-occurrence based on the social ties and habits similarities. ...
Location-based social network (LBSN) is at the forefront of emerging trends in social network services (SNS) since the users in LBSN are allowed to "check-in" the places (locations) when they visit them ...
Conclusion In this paper, we present a study of exploring spatio-temporal features of user's activities to predict co-occurrence in a location-based social network, Gowalla. ...
doi:10.1007/s11704-013-3902-8
fatcat:nnjda23aebgklpwnzowip2hcw4
Inferring Friendship from Check-in Data of Location-Based Social Networks
2015
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15
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With the ubiquity of GPS-enabled devices and location-based social network services, research on human mobility becomes quantitatively achievable. ...
The second model proposes a solution for predicting friendship of two individuals based on all their co-occurred places. ...
Moreover, a new type of social network services has emerged, namely Location-based social networks (LBSNs). ...
doi:10.1145/2808797.2808884
dblp:conf/asunam/ChengPZ15
fatcat:wbuoqnptzneo5nyiunci3mz7lq
Predicting participants in public events using stock photos
2012
Proceedings of the 20th ACM international conference on Multimedia - MM '12
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In this paper, we study a corpus of approximately 9 million stock photographs taken over a 10 year period and, using their metadata, we extract a social network from co-appearance of public figures in ...
We exploit this latent social information and combine it with the rich image metadata to explore the possibility of predicting attendees at future events, showing promising performance for this task. ...
CONCLUSIONS In this paper we build social networks based on photo and event co-occurrence in a corpus of 9M stock photos. ...
doi:10.1145/2393347.2396391
dblp:conf/mm/OHareAJ12
fatcat:ul5qp4glbzgg5lyrnjxfmvg4te
Discovering Local Social Groups using Mobility Data
2015
International Journal of Computer Applications
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First we modify existing co-location algorithms to take the significance of the location of co-occurrence into account in predicting relationship strength. ...
Next, we propose a system to identify social groups that exists in geographic areas called Local Social Groups by using co-location information. ...
In this paper we use filter the data based on the significance of the location of co-occurrence. ...
doi:10.5120/21351-4042
fatcat:deolh26zhvambh6zmwfpytndo4
Academic failures and co-location social networks in campus
2022
EPJ Data Science
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This paper focuses on the associations between academic failures, that defined by not passing course exams, and campus social networks based on students' co-location occurrences. ...
Additionally, we show that messages reflected in co-location social networks and behavioral activities indeed help predict failures and the network snapshot at mid-term offers competent prediction power ...
The limitation of this study lies in the fact the co-location social networks are inferred based on high-frequency co-occurrences in smart-card system. ...
doi:10.1140/epjds/s13688-022-00322-0
fatcat:pmktt42oj5aptd466iy42ull4a
EBM
2013
Proceedings of the 2013 international conference on Management of data - SIGMOD '13
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We examine two independent ways: diversity and weighted frequency, through which co-occurrences contribute to social strength. ...
In this paper, we are interested in inferring these social connections by analyzing people's location information, which is useful in a variety of application domains from sales and marketing to intelligence ...
(e.g., location popularity). • We evaluated EBM using a large real-world dataset collected by a location-based social network called Gowalla. ...
doi:10.1145/2463676.2465301
dblp:conf/sigmod/PhamSL13
fatcat:apykdgwumbgordrtpvhuhfegxa
Exploring homophily in demographics and academic performance using spatial-temporal student networks
2020
Educational Data Mining
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However, a large part of students' social connections through day-to-day oncampus encounters has remained underexplored. ...
A tie in the spatialtemporal network was inferred when two individuals connected to the same WiFi access point at the same time intervals at the 'beyond chance' frequency. ...
In line with previous research on location-based networks [15, 16] , social ties between WiFi users can be inferred from spatial and temporal co-occurrences (i.e. two users connected to the same WiFi ...
dblp:conf/edm/NguyenPBL20
fatcat:q3g32ryzhbagzad53mdri4t2ha
Tie Strength in Online Social Networks and its Applications: A Brief Study
[article]
2020
arXiv
pre-print
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In online social network (OSN), understanding the factors bound to the role and strength of interaction(tie) are essential to model a wide variety of network-based applications. ...
Finally, a set of future challenges of the tie strength in online social networks is discussed. ...
[30] proposed an entropy-based model for estimating tie strength based on co-occurence of individuals. Sadilek et al. [34] conferred location prediction approach based on social tie strength. ...
arXiv:2002.07608v2
fatcat:2mehz44vhnaovgnrz65o7zodxi
GeoSocial Data Analytics
[chapter]
2017
Encyclopedia of GIS
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Synonyms Friendships; Implicit social connections; Social strength Definition The ubiquity of mobile devices has enabled Location-Based Social Networks (LBSN), such as Foursquare and Twitter, to collect ...
Thus, the goal is to derive the implicit social network of people and the social strength from their real-world location data as opposed to or in addition to their online activities. ...
That is, it is the amount of location information in the co-occurrences of two users; the more locations, the more information it contains, therefore the less predictable one can make a guess about the ...
doi:10.1007/978-3-319-17885-1_1566
fatcat:y4i27pxvifhllbm2g7hgdtd6hq
GeoSocial Data Analytics
[chapter]
2015
Encyclopedia of GIS
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Synonyms Friendships; Implicit social connections; Social strength Definition The ubiquity of mobile devices has enabled Location-Based Social Networks (LBSN), such as Foursquare and Twitter, to collect ...
Thus, the goal is to derive the implicit social network of people and the social strength from their real-world location data as opposed to or in addition to their online activities. ...
That is, it is the amount of location information in the co-occurrences of two users; the more locations, the more information it contains, therefore the less predictable one can make a guess about the ...
doi:10.1007/978-3-319-23519-6_1566-1
fatcat:ssupxuwp2bcurhpyj5ep457bt4
Mobile Homophily and Social Location Prediction
[article]
2015
arXiv
pre-print
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Using a large LBSN dataset, his paper investigates the interdependency between human mobility and social proximity, the influence of social networks on enhancing location prediction of an individual and ...
may be more dominated by routines and habitual movement patterns, resulting in a more predictable mobility behavior on the basis of their own location history while, in contrast, extrovert users get about ...
In a first part we focus on studying the correlations between social relations and mobile homophily, using a large dataset from a location based social network (LBSN). ...
arXiv:1506.07763v1
fatcat:eikc3cfvgbg7fi4a24mwncxwzu
Look inside. Predicting stock prices by analysing an enterprise intranet social network and using word co-occurrence networks
2019
International Journal of Entrepreneurship and Small Business
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2021 pre-print arXiv:2105.11780v1 fatcat:7zd3aypqezbhfoqut4wixurp2q
We found that a lower sentiment, a higher betweenness centrality of the company brand, a denser word co-occurrence network and more equally distributed centrality scores of employees (lower group betweenness ...
Lastly, we contribute to the research on word co-occurrence networks by extending their field of application. ...
In our explorative study, we created a word co-occurrence network, considering the messages extracted from the intranet forum of a large Italian company and the co-occurrence of these words. ...
doi:10.1504/ijesb.2019.098986
fatcat:4imig5qo3rgrvj65umpbvxepu4
Social Network Discovery by Mining Spatio-Temporal Events
2005
Computational and mathematical organization theory
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In this paper, we propose a model for constructing a social network from events, and provide an algorithm that mines these events from the data. ...
Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products, ...
Acknowledgment We would like to thank the Centre for IT Services, Nanyang Technological University, for providing us with the experimental data used in this paper. ...
doi:10.1007/s10588-005-3939-9
fatcat:bhuevyw7vze6pclpmapinl2mfa
Familiar Strangers: the Collective Regularity in Human Behaviors
[article]
2018
arXiv
pre-print
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a social network. ...
The social phenomenon of familiar strangers was identified by Stanley Milgram in 1972 with a small-scale experiment. ...
Crandall (2010) , has the similar observation on a large-scale data, in particular, a minimal number of co-occurrences results in a high likelihood of a social tie, the negation of which may induce noises ...
arXiv:1803.08955v2
fatcat:wnr4ememrvbjjgjx77uz63kpry
Location Based Social Networks - Definition, Current State of the Art and Research Agenda
2013
Transactions on GIS
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Within these Location Based Social Networks vast amounts of geographic information are allocated, which attracted the attention of researches with various scientific backgrounds. ...
This paper presents a comprehensive definition of this special type of Social Network Sites and an overview of research activities, which are currently conducted using the data. ...
Second, the prediction of social ties between members of an online social network community based on relative geographic distance on the one hand and further based the on number of co-location occurrences ...
doi:10.1111/tgis.12032
fatcat:plrjoafm7vcutfeieoss7jruqq
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