{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:47:15Z","timestamp":1760240835497,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,9,16]],"date-time":"2019-09-16T00:00:00Z","timestamp":1568592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Recently, social networks have shown huge potential in terms of collaborative web services and the study of peer influence as a result of the massive amount of data, datasets, and interrelations generated. These interrelations cannot guarantee the success of online social networks without ensuring the existence of trust between nodes. Detecting influential nodes improves collaborative filtering (CF) recommendations in which nodes with the highest influential capability are most likely to be the source of recommendations. Although CF-based recommendation systems are the most widely used approach for implementing recommender systems, this approach ignores the mutual trust between users. In this paper, a trust-based algorithm (TBA) is introduced to detect influential spreaders in social networks efficiently. In particular, the proposed TBA estimates the influence that each node has on the other connected nodes as well as on the whole network. Next, a Friend-of-Friend recommendation (FoF-SocialI) algorithm is addressed to detect the influence of social ties in the recommendation process. Finally, experimental results, performed on three large scale location-based social networks, namely, Brightkite, Gowalla, and Weeplaces, to test the efficiency of the proposed algorithm, are presented. The conducted experiments show a remarkable enhancement in predicting and recommending locations in various social networks.<\/jats:p>","DOI":"10.3390\/ijgi8090415","type":"journal-article","created":{"date-parts":[[2019,9,17]],"date-time":"2019-09-17T03:31:46Z","timestamp":1568691106000},"page":"415","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Exploring Trusted Relations among Virtual Interactions in Social Networks for Detecting Influence Diffusion"],"prefix":"10.3390","volume":"8","author":[{"given":"Heba M.","family":"Wagih","sequence":"first","affiliation":[{"name":"Information Systems Department, The British University in Egypt, El Shorouk City, Cairo 11837, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hoda M. O.","family":"Mokhtar","sequence":"additional","affiliation":[{"name":"Information Systems Department, Cairo University, Cairo 12613, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7327-4983","authenticated-orcid":false,"given":"Samy S.","family":"Ghoniemy","sequence":"additional","affiliation":[{"name":"Computer Networks Department, The British University in Egypt, El Shorouk City, Cairo 11837, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1007\/s12599-010-0127-3","article-title":"A Critical Review of Centrality Measures in Social Networks","volume":"2","author":"Landherr","year":"2010","journal-title":"Bus. Inf. Syst. Eng."},{"key":"ref_2","unstructured":"Alvarez-Hamelin, J.I., Dall\u2019Asta, L., Barrat, A., and Vespignani, A. (2005, January 5\u20138). Large Scale Networks Fingerprinting and Visualization Using the K-core Decomposition. Proceedings of the 18th International Conference on Neural Information Processing Systems, Vancouver, BC, Canada."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ver Steeg, G., and Galstyan, A. (2012, January 16\u201320). Information Transfer in Social Media. Proceedings of the 21st International Conference on World Wide Web, Lyon, France.","DOI":"10.1145\/2187836.2187906"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Yang, J., and Leskovec, J. (2010, January 13\u201317). Modeling Information Diffusion in Implicit Networks. Proceedings of the 2010 IEEE International Conference on Data Mining, Sydney, Australia.","DOI":"10.1109\/ICDM.2010.22"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ye, S., and Wu, S.F. (2010, January 27\u201329). Measuring Message Propagation and Social Influence on Twitter. Com. In Proceedings of the Second International Conference on Social Informatics, Laxenburg, Austria.","DOI":"10.1007\/978-3-642-16567-2_16"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Bonchi, F. (2011, January 22\u201327). Influence Propagation in Social Networks: A Data Mining Perspective. Proceedings of the 2011 IEEE\/WIC\/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Lyon, France.","DOI":"10.1109\/WI-IAT.2011.292"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zhao, X., Liu, F., Wang, J., and Li, T. (2017). Evaluating Influential Nodes in Social Networks by Local Centrality with a Coefficient. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6020035"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13278-016-0416-z","article-title":"Recommendation information diffusion in social networks considering user influence and semantics","volume":"6","author":"Margaris","year":"2016","journal-title":"Soc. Netw. Anal. Min."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Margaris, D., Vassilakis, C., and Georgiadis, P. (2017). Knowledge-Based Leisure Time Recommendations in Social Networks. Current Trends on Knowledge-Based Systems: Theory and Applications, Springer.","DOI":"10.1007\/978-3-319-51905-0_2"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1145\/2981545","article-title":"Using Centrality Measures to Predict Helpfulness-Based Reputation in Trust Networks","volume":"17","author":"Meo","year":"2017","journal-title":"ACM Trans. Internet Technol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.ins.2016.08.023","article-title":"Social influence modeling using information theory in mobile social networks","volume":"379","author":"Peng","year":"2017","journal-title":"Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Adali, S., Escriva, R., Goldberg, M.K., Hayvanovych, M., Magdon-Ismail, M., Szymanski, B.K., Wallace, W.A., and Williams, G. (2010, January 23\u201326). Measuring behavioral trust in social networks. Proceedings of the IEEE International Conference on Intelligence and Security Informatics, Vancouver, BC, Canada.","DOI":"10.1109\/ISI.2010.5484757"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Song, H., Pei, Q., Xiao, Y., Li, Z., and Wag, Y. (2017, January 16\u201319). A Novel Recommendation Model Based on Trust Relations and Item Ratings in Social Networks. Proceedings of the 2017 International Conference on Networking and Network Applications (NaNA), Kathmandu, Nepal.","DOI":"10.1109\/NaNA.2017.17"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Bao, J., Zheng, Y., and Mokbel, M.F. (2012, January 6\u20139). Location-based and Preference-aware Recommendation Using Sparse Geo-social Networking Data. Proceedings of the 20th International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA.","DOI":"10.1145\/2424321.2424348"},{"key":"ref_15","unstructured":"Hakan, B., and Pinar, K. (2016, January 11\u201315). Context-Aware Friend Recommendation for Location Based Social Networks Using Random Walk. Proceedings of the 25th International Conference Companion on World Wide Web, Montreal, QC, Canada."},{"key":"ref_16","unstructured":"Hangal, S., MacLean, D., Lam, M.S., and Heer, J. (2010, January 25\u201328). All Friends are not Equal: Using Weights in Social Graphs to Improve Search. Proceedings of the Workshop on Social Network Mining & Analysis, ACM SIGKDD, Washington, DC, USA."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wagih, H.M., Mokhtar, H.M.O., and Ghoniemy, S.S. (2017, January 14\u201315). Location Recommendation Based on Social Trust. Proceedings of the 13th International Conference on Semantics, Knowledge and Grids (SKG), Beijing, China.","DOI":"10.1109\/SKG.2017.00017"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kim, H., Beznosov, K., and Yoneki, E. (2014, January 7\u201311). Finding Influential Neighbors to Maximize Information Diffusion in Twitter. Proceedings of the 23rd International Conference on World Wide Web, Seoul, Korea.","DOI":"10.1145\/2567948.2579358"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.knosys.2013.01.017","article-title":"Identifying Influential Nodes in Complex Networks with Community Structure","volume":"42","author":"Zhang","year":"2013","journal-title":"Knowl.-Based Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1109\/TASE.2010.2052042","article-title":"A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks","volume":"8","author":"Narayanam","year":"2011","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Rossi, M., Malliaros, F.D., and Vazirgiannis, M. (2015, January 18\u201322). Spread It Good, Spread It Fast: Identification of Influential Nodes in Social Networks. Proceedings of the 24th International Conference on World Wide Web, Florence, Italy.","DOI":"10.1145\/2740908.2742736"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"19307","DOI":"10.1038\/srep19307","article-title":"Locating influential nodes in complex networks","volume":"6","author":"Malliaros","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Basuchowdhuri, P., and Majumder, S. (2014, January 13\u201315). Finding Influential Nodes in Social Networks Using Minimum k-Hop Dominating Set. Proceedings of the First, International Conference on Applied Algorithms, Kolkata, India.","DOI":"10.1007\/978-3-319-04126-1_12"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1850118","DOI":"10.1142\/S0217979218501187","article-title":"Identifying and ranking influential spreaders in complex networks by combining a local-degree sum and the clustering coefficient","volume":"32","author":"Mengtian","year":"2018","journal-title":"Int. J. Modern Phys. B"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Goyal, A., Bonchi, F., and Lakshmanan, L.V.S. (2008, January 26\u201330). Discovering Leaders from Community Actions. Proceedings of the 17th ACM Conference on Information and Knowledge Management, Napa Valley, CA, USA.","DOI":"10.1145\/1458082.1458149"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.osnem.2018.05.001","article-title":"Social trust model for rating prediction in recommender systems: Effects of similarity, centrality, and social ties","volume":"7","author":"Davoudi","year":"2018","journal-title":"Online Soc. Netw. Media"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Yang, J., and Leskovec, J. (2013, January 4\u20138). Overlapping Community Detection at Scale: A Nonnegative Matrix Factorization Approach. Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, Rome, Italy.","DOI":"10.1145\/2433396.2433471"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wei, H., Pan, Z., Hu, G., Zhang, L., Yang, H., Li, X., and Zhou, X. (2018). Identifying influential nodes based on network representation learning in complex networks. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0200091"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3200","DOI":"10.1103\/PhysRevLett.86.3200","article-title":"Epidemic spreading in scale-free networks","volume":"86","author":"Romualdo","year":"2001","journal-title":"Phys. Rev. Lett."},{"key":"ref_30","first-page":"246","article-title":"Regression towards mediocrity in hereditary stature","volume":"15","author":"Galton","year":"1886","journal-title":"J. Anthropol. Insti. Great Br. Irel."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"324","DOI":"10.14778\/2856318.2856327","article-title":"Ego-net Community Mining Applied to Friend Suggestion","volume":"9","author":"Epasto","year":"2015","journal-title":"Proc. VLDB Endow."},{"key":"ref_32","unstructured":"Leskovec, J., and Krevl, A. (2014, June 20). SNAP Datasets: Stanford Large Network Dataset Collection. Available online: https:\/\/snap.stanford.edu\/data."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Liu, Y., Wei, W., Sun, A., and Miao, C. (2014, January 3\u20137). Exploiting Geographical Neighborhood Characteristics for Location Recommendation. Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM 14), Shanghai, China.","DOI":"10.1145\/2661829.2662002"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/9\/415\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:20:32Z","timestamp":1760188832000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/9\/415"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,16]]},"references-count":33,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["ijgi8090415"],"URL":"https:\/\/doi.org\/10.3390\/ijgi8090415","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2019,9,16]]}}}