{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T21:06:20Z","timestamp":1761599180876,"version":"3.41.0"},"reference-count":49,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2019,4,11]],"date-time":"2019-04-11T00:00:00Z","timestamp":1554940800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"TCS","award":["PhD Fellowship"],"award-info":[{"award-number":["PhD Fellowship"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2019,5,31]]},"abstract":"<jats:p>\n            Location-based social networks (LBSNs) such as Foursquare offer a platform for users to share and be aware of each other\u2019s physical movements. As a result of such a sharing of\n            <jats:italic>check-in<\/jats:italic>\n            information with each other, users can be influenced to visit (or check-in) at the locations visited by their friends. Quantifying such influences in these LBSNs is useful in various settings such as location promotion, personalized recommendations, mobility pattern prediction, and so forth. In this article, we develop a model to quantify the influence specific to a location between a pair of users. Specifically, we develop a framework called\n            <jats:italic>LoCaTe<\/jats:italic>\n            , that combines (a) a user mobility model based on kernel density estimates; (b) a model of the semantics of the location using topic models; and (c) a user correlation model that uses an exponential distribution. We further develop\n            <jats:italic>LoCaTe+<\/jats:italic>\n            , an advanced model within the same framework where user correlation is quantified using a Mutually Exciting Hawkes Process. We show the applicability of\n            <jats:italic>LoCaTe<\/jats:italic>\n            and\n            <jats:italic>LoCaTe+<\/jats:italic>\n            for location promotion and location recommendation tasks using LBSNs. Our models are validated using a long-term crawl of Foursquare data collected between January 2015 and February 2016, as well as other publicly available LBSN datasets. Our experiments demonstrate the efficacy of the LoCaTe framework in capturing location-specific influence between users. We also show that our models improve over state-of-the-art models for the task of location promotion as well as location recommendation.\n          <\/jats:p>","DOI":"10.1145\/3300199","type":"journal-article","created":{"date-parts":[[2019,4,12]],"date-time":"2019-04-12T13:29:11Z","timestamp":1555075751000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Location-Specific Influence Quantification in Location-Based Social Networks"],"prefix":"10.1145","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4474-9868","authenticated-orcid":false,"given":"Ankita","family":"Likhyani","sequence":"first","affiliation":[{"name":"IIIT Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Srikanta","family":"Bedathur","sequence":"additional","affiliation":[{"name":"IIT Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deepak","family":"P.","sequence":"additional","affiliation":[{"name":"Queen's University Belfast, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,4,11]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2433396.2433403"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/944919.944937"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2666310.2666489"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2006.11.007"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835934"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020579"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505616"},{"key":"e_1_2_1_8_1","volume-title":"Proceedings of the 6th AAAI International Conference on Weblogs and Social Media (ICWSM'12)","author":"Gao Huiji","year":"2012","unstructured":"Huiji Gao , Jiliang Tang , and Huan Liu . 2012 . Exploring social-historical ties on location-based social networks . In Proceedings of the 6th AAAI International Conference on Weblogs and Social Media (ICWSM'12) . The AAAI Press. Huiji Gao, Jiliang Tang, and Huan Liu. 2012. Exploring social-historical ties on location-based social networks. In Proceedings of the 6th AAAI International Conference on Weblogs and Social Media (ICWSM'12). The AAAI Press."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1718487.1718518"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/58.1.83"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2905373"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956769"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/11523468_91"},{"key":"e_1_2_1_14_1","volume-title":"Pollett","author":"Laub Patrick J.","year":"2015","unstructured":"Patrick J. Laub , Thomas Taimre , and Philip K . Pollett . 2015 . 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Social Media and its Implications for Viral Marketing.  Rohan Miller and Natalie Lammas. 2010. Social Media and its Implications for Viral Marketing."},{"key":"e_1_2_1_26_1","first-page":"2","article-title":"Use of social media in health promotion: Purposes, key performance indicators, and evaluation metrics","volume":"13","author":"Neiger Brad L.","year":"2012","unstructured":"Brad L. Neiger , Rosemary Thackeray , Sarah A. van Wagenen , Carl L. Hanson , Joshua H. West , Michael D. Barnes , and Michael C. Fagen . 2012 . Use of social media in health promotion: Purposes, key performance indicators, and evaluation metrics . Health Promotion Pract. 13 , 2 (Jan. 2012), 159--164. Brad L. Neiger, Rosemary Thackeray, Sarah A. van Wagenen, Carl L. Hanson, Joshua H. West, Michael D. Barnes, and Michael C. Fagen. 2012. Use of social media in health promotion: Purposes, key performance indicators, and evaluation metrics. 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