A study on features of social recommender systems

  • Jyoti ShokeenEmail author
  • Chhavi Rana


Recommender system is an emerging field of research with the advent of World Wide Web and E-commerce. Recently, an increasing usage of social networking websites plausibly has a great impact on diverse facets of our lives in different ways. Initially, researchers used to consider recommender system and social networks as independent topics. With the passage of time, they realized the importance of merging the two to produce enhanced recommendations. The integration of recommender system with social networks produces a new system termed as social recommender system. In this study, we initially describe the concept of recommender system and social recommender system and then investigates different features of social networks that play a major role in generating effective recommendations. Each feature plays an essential role in giving good recommendations and resolving the issues of traditional recommender systems. Lastly, this paper also discusses future work in this area that can aid in enriching the quality of social recommender systems.


Recommender system Social recommender system Cold-start Collaborative filtering Social networks Information overload 



The first author of the paper likes to say thanks to Council of Scientific and Industrial Research (CSIR) to receive financial assistance in the form of JRF.


  1. Abbasi MA, Tang J, Liu H (2014) Trust-aware recommender systems. Machine learning book on computational trust. Chapman & Hall/CRC Press, Boca RatonGoogle Scholar
  2. Adomavicius G, Tuzhilin A (2011) Context-aware recommender systems. Recommender systems handbook. Springer, Boston, pp 217–253Google Scholar
  3. Aggarwal CC (2016) Knowledge-based recommender systems. Recommender systems. Springer, Cham, pp 167–197Google Scholar
  4. Al-Shamri MYH (2016) User profiling approaches for demographic recommender systems. Knowl Based Syst 100:175–187. Google Scholar
  5. Arnaboldi V, Campana MG, Delmastro F, Pagani E (2016) PLIERS: a popularity-based recommender system for content dissemination in online social networks. In: Proceedings of the 31st annual ACM symposium on applied computing, ACM, pp 671–673Google Scholar
  6. Au Yeung Cm, Iwata T (2011) Strength of social influence in trust networks in product review sites. In: Proceedings of the fourth ACM international conference on web search and data mining, ACM, pp 495–504Google Scholar
  7. Bao J, Zheng Y, Wilkie D, Mokbel M (2015) Recommendations in location-based social networks: a survey. GeoInformatica 19(3):525–565Google Scholar
  8. Beel J, Gipp B, Langer S, Breitinger C (2016) Paper recommender systems: a literature survey. Int J Digit Libr 17(4):305–338Google Scholar
  9. Bellman S, Lohse GL, Johnson EJ (1999) Predictors of online buying behavior. Commun ACM 42(12):32–38. Google Scholar
  10. Bobadilla J, Ortega F, Hernando A, Gutiérrez A (2013) Recommender systems survey. Knowl Based Syst 46:109–132. Google Scholar
  11. Burke R (2002) Hybrid recommender systems: survey and experiments. User Model User Adapt Interact 12(4):331–370zbMATHGoogle Scholar
  12. Burke R (2007) Hybrid web recommender systems. The adaptive web. Springer, Berlin, pp 377–408Google Scholar
  13. Capdevila J, Arias M, Arratia A (2016) GeoSRS: a hybrid social recommender system for geolocated data. Inform Syst 57:111–128Google Scholar
  14. Carrasco AL, et al. (2012) Towards trust-aware recommendations in social networks. Ph.D. thesis, Master Thesis, Polytechnic University of Catalonia, SpainGoogle Scholar
  15. Chirita PA, Costache S, Nejdl W, Handschuh S (2007) P-tag: large scale automatic generation of personalized annotation tags for the web. In: Proceedings of the 16th international conference on world wide web, ACM, pp 845–854Google Scholar
  16. Christensen I, Schiaffino S, Armentano M (2016) Social group recommendation in the tourism domain. J Intell Inform Syst 47(2):209–231Google Scholar
  17. Codina V, Ceccaroni L (2010) Taking advantage of semantics in recommendation systems. In: Artificial intelligence research and development: proceedings of the 13th international conference of the Catalan association for artificial intelligence, IOS Press, vol 220, p 163Google Scholar
  18. Colombo-Mendoza LO, Valencia-García R, Rodríguez-González A, Colomo-Palacios R, Alor-Hernández G (2018) Towards a knowledge-based probabilistic and context-aware social recommender system. J Inform Sci 44(4):464–490. Google Scholar
  19. Cui L, Sun L, Fu X, Lu N, Zhang G (2017) Exploring a trust based recommendation approach for videos in online social network. J Signal Process Syst 86(2–3):207–219. Google Scholar
  20. Dakhel AM, Malazi HT, Mahdavi M (2018) A social recommender system using item asymmetric correlation. Appl Intell 48(3):527–540. Google Scholar
  21. Dang QV, Ignat CL (2017) dTrust: a deep learning approach for social recommendation. In: 2007 IEEE 3rd international conference on collaboration and internet computing (CIC), IEEE, pp 209–218,
  22. Davoodi E, Kianmehr K, Afsharchi M (2013) A semantic social network-based expert recommender system. Appl Intell 39(1):1–13Google Scholar
  23. De Pessemier T, Dooms S, Deryckere T, Martens L (2010) Time dependency of data quality for collaborative filtering algorithms. In: Proceedings of the fourth ACM conference on recommender systems, ACM, pp 281–284Google Scholar
  24. Dey AK, Abowd GD, Wood A (1998) CyberDesk: a framework for providing self-integrating context-aware services. Knowl Based Syst 11(1):3–13. Google Scholar
  25. Ekstrand MD, Riedl JT, Konstan JA (2011) Collaborative filtering recommender systems. Found Trends® Hum Comput Interact 4(2):81–173. Google Scholar
  26. Farooq U, Song Y, Carroll JM, Giles CL (2007) Social bookmarking for scholarly digital libraries. IEEE Internet Comput 11(6):29–35. Google Scholar
  27. Farseev A, Kotkov D, Semenov A, Veijalainen J, Chua TS (2015) Cross-social network collaborative recommendation. In: Proceedings of the ACM Web science conference, ACM, p 38Google Scholar
  28. Frikha M, Mhiri M, Gargouri F (2015) Designing a user interest ontology-driven social recommender system: application for tunisian tourism. Advances in intelligent systems and computing, Springer, Cham, pp 159–166Google Scholar
  29. Gao H, Tang J, Hu X, Liu H (2013) Exploring temporal effects for location recommendation on location-based social networks. In: Proceedings of the 7th ACM conference on recommender systems, ACM, pp 93–100Google Scholar
  30. Gao P, Baras JS, Golbeck J (2015) Trust-aware social recommender system design. In: Doctor consortium of 2015 international conference on information systems security and privacy, pp 19–28Google Scholar
  31. Gottapu RD, Monangi LVS (2017) Point-of-interest recommender system for social groups. Proc Comput Sci 114:159–164. Google Scholar
  32. Guo C, Li B, Tian X (2016) Flickr group recommendation using rich social media information. Neurocomputing 204:8–16. Google Scholar
  33. Gurini D, Gasparetti F, Micarelli A, Sansonetti G (2018) Temporal people-to-people recommendation on social networks with sentiment-based matrix factorization. Futur Generat Comput Syst 78:430–439. Google Scholar
  34. He J, Chu WW (2010) A social network-based recommender system (SNRS). Data mining for social network data. Springer, Boston, pp 47–74Google Scholar
  35. Hong M, Jung JJ, Camacho D (2017) GRSAT: a novel method on group recommendation by social affinity and trustworthiness. Cybern Syst 48(3):140–161Google Scholar
  36. Huang CL, Yeh PH, Lin CW, Wu DC (2014) Utilizing user tag-based interests in recommender systems for social resource sharing websites. Knowl-Based Syst 56:86–96Google Scholar
  37. Huang Z, Chung W, Ong TH, Chen H (2002) A graph-based recommender system for digital library. In: Proceedings of the 2nd ACM/IEEE-CS joint conference on digital libraries, ACM, pp 65–73Google Scholar
  38. Isinkaye F, Folajimi Y, Ojokoh B (2015) Recommendation systems: principles, methods and evaluation. Egypt Inform J 16(3):261–273. Google Scholar
  39. Jiang M, Cui P, Chen X, Wang F, Zhu W, Yang S (2015) Social recommendation with cross-domain transferable knowledge. IEEE Trans Knowl Data Eng 27(11):3084–3097Google Scholar
  40. Kefalas P, Symeonidis P, Manolopoulos Y (2018) Recommendations based on a heterogeneous spatio-temporal social network. World Wide Web 21(2):345–371Google Scholar
  41. Khan MM, Ibrahim R, Ghani I (2017) Cross domain recommender systems: a systematic literature review. ACM Comput Surv (CSUR) 50(3):36Google Scholar
  42. Koren Y (2009) Collaborative filtering with temporal dynamics. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, pp 447–456Google Scholar
  43. Lašek I, Vojtáš P (2011) Semantic information filtering-beyond collaborative filtering. In: 4th international semantic search workshopGoogle Scholar
  44. Li CY, Lin SD (2014) Matching users and items across domains to improve the recommendation quality. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, pp 801–810Google Scholar
  45. Li YM, Wu CT, Lai CY (2013) A social recommender mechanism for e-commerce: combining similarity, trust, and relationship. Decis Support Syst 55(3):740–752Google Scholar
  46. Liao G, Jiang S, Zhou Z, Wan C, Liu X (2018) POI recommendation of location-based social networks using tensor factorization. In: 2018 19th IEEE international conference on mobile data management (MDM), pp 116–124,
  47. Linden G, Smith B, York J (2003) Amazon. com recommendations: item-to-item collaborative filtering. IEEE Internet comput 7(1):76–80Google Scholar
  48. Liu B, Xiong H (2013) Point-of-interest recommendation in location based social networks with topic and location awareness. In: Proceedings of the 2013 SIAM international conference on data mining, SIAM, pp 396–404Google Scholar
  49. Liu B, Fu Y, Yao Z, Xiong H (2013a) Learning geographical preferences for point-of-interest recommendation. In: Proceedings of the 19th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, pp 1043–1051Google Scholar
  50. Liu NN, He L, Zhao M (2013b) Social temporal collaborative ranking for context aware movie recommendation. ACM Trans Intell Syst Technol (TIST) 4(1):15Google Scholar
  51. Liu X, Aberer K (2013) SoCo: a social network aided context-aware recommender system. In: Proceedings of the 22nd international conference on world wide web, ACM, pp 781–802Google Scholar
  52. Liu Y, Wang S, Khan MS, He J (2018) A novel deep hybrid recommender system based on auto-encoder with neural collaborative filtering. Big Data Min Anal 1(3):211–221. Google Scholar
  53. Ma G, Wang Y, Zheng X, Wang M (2018) Leveraging transitive trust relations to improve cross-domain recommendation. IEEE Access 6:38012–38025Google Scholar
  54. Ma H, Zhou D, Liu C, Lyu MR, King I (2011) Recommender systems with social regularization. In: Proceedings of the fourth ACM international conference on web search and data mining, ACM, pp 287–296Google Scholar
  55. Macedo AQ, Marinho LB, Santos RL (2015) Context-aware event recommendation in event-based social networks. In: Proceedings of the 9th ACM conference on recommender systems, ACM, pp 123–130Google Scholar
  56. Manasa S, Manjula S, Venugopal K (2017) Trust aware system for social networks: a comprehensive survey. Int J Comput Appl 162(5):34–43Google Scholar
  57. Massa P, Avesani P (2007) Trust-aware recommender systems. In: Proceedings of the 2007 ACM conference on recommender systems, ACM, pp 17–24Google Scholar
  58. Masthoff J (2011) Group recommender systems: Combining individual models. Recommender systems handbook. Springer, Boston, pp 677–702Google Scholar
  59. Melville P, Sindhwani V (2011) Recommender systems. Encyclopedia of machine learning. Springer, Boston, pp 829–838Google Scholar
  60. Milicevic AK, Nanopoulos A, Ivanovic M (2010) Social tagging in recommender systems: a survey of the state-of-the-art and possible extensions. Artif Intell Rev 33(3):187–209Google Scholar
  61. Pagano R, Cremonesi P, Larson M, Hidasi B, Tikk D, Karatzoglou A, Quadrana M (2016) The contextual turn: From context-aware to context-driven recommender systems. In: Proceedings of the 10th ACM conference on recommender systems, ACM, pp 249–252Google Scholar
  62. Pan R, Dolog P, Xu G (2012) KNN-based clustering for improving social recommender systems. International workshop on agents and data mining interaction. Springer, Berlin, pp 115–125Google Scholar
  63. Perugini S, Gonçalves MA, Fox EA (2004) Recommender systems research: a connection-centric survey. J Intell Inform Syst 23(2):107–143zbMATHGoogle Scholar
  64. Pham TAN, Li X, Cong G, Zhang Z (2015) A general graph-based model for recommendation in event-based social networks. In: 2015 IEEE 31st international conference on Data engineering (ICDE), IEEE, pp 567–578Google Scholar
  65. Quijano-Sanchez L, Recio-Garcia JA, Diaz-Agudo B, Jimenez-Diaz G (2013) Social factors in group recommender systems. ACM Trans Intell Syst Technol (TIST) 4(1):8Google Scholar
  66. Rana C, Jain SK (2015) A study of the dynamic features of recommender systems. Artif Intell Rev 43(1):141–153Google Scholar
  67. Sarwar B, Karypis G, Konstan J, Riedl J (2001) Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th international conference on world wide web, ACM, pp 285–295Google Scholar
  68. Sassi IB, Mellouli S, Yahia SB (2017) Context-aware recommender systems in mobile environment: On the road of future research. Inform Syst 72:27–61. Google Scholar
  69. Sellami K, Ahmed-Nacer M, Tiako P (2014) From social network to semantic social network in recommender system. arXiv preprint arXiv:1407.3392
  70. Shen Y, Lv T, Chen X, Wang Y (2016) A collaborative filtering based social recommender system for e-commerce. Int J Simul Syst Sci Technol 17(22):91–96Google Scholar
  71. Shokeen J (2018) On measuring the role of social networks in project recommendation. Int J Comput Sci Eng 6(4):215–219. Google Scholar
  72. Shokeen J, Rana C (2018a) A review on the dynamics of social recommender systems. Int J Web Eng Technol 13(3):255–276Google Scholar
  73. Shokeen J, Rana C (2018b) A study on trust-aware social recommender systems. In: 2018 5th International conference on computing for sustainable global development, IEEE, pp 4268–4272Google Scholar
  74. Shokeen J, Rana C, Sehrawat H (2019) A novel approach for community detection using the label propagation technique. In: Integrated intelligent computing, communication and security. Springer, Singapore, pp 127–132
  75. Song Y, Zhang L, Giles CL (2011) Automatic tag recommendation algorithms for social recommender systems. ACM Trans Web (TWEB) 5(1):4Google Scholar
  76. Su X, Khoshgoftaar TM (2009) A survey of collaborative filtering techniques. Adv Artif intell 2009:1–19. Google Scholar
  77. Sulieman D, Malek M, Kadima H, Laurent D (2016) Toward social-semantic recommender systems. Int J Inform Syst Soc Chang 7(1):1–30. Google Scholar
  78. Tang J, Gao H, Liu H (2012) mTrust: discerning multi-faceted trust in a connected world. In: Proceedings of the fifth ACM international conference on web search and data mining, ACM, pp 93–102Google Scholar
  79. Tang J, Hu X, Liu H (2013) Social recommendation: a review. Soc Netw Anal Min 3(4):1113–1133Google Scholar
  80. Tarus JK, Niu Z, Mustafa G (2018) Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning. Artif Intell Rev 50(1):21–48Google Scholar
  81. Tian H, Liang P (2017) Improved recommendations based on trust relationships in social networks. Futur Internet 9(1):9. Google Scholar
  82. Wang M, Ma J (2016) A novel recommendation approach based on users weighted trust relations and the rating similarities. Soft Comput 20(10):3981–3990Google Scholar
  83. Wang X, He X, Nie L, Chua TS (2017) Item silk road: Recommending items from information domains to social users. In: Proceedings of the 40th international ACM SIGIR conference on research and development in information retrieval, ACM, pp 185–194Google Scholar
  84. Wang Y, Chan SCF, Ngai G (2012) Applicability of demographic recommender system to tourist attractions: a case study on trip advisor. In: Proceedings of the the 2012 IEEE/WIC/ACM international joint conferences on web intelligence and intelligent agent technology-Volume 03, IEEE computer society, pp 97–101Google Scholar
  85. Wei X, Huang H, Xin X, Yang X (2013) Distinguishing social ties in recommender systems by graph-based algorithms. In: International conference on web information systems engineering, Springer, pp 219–228Google Scholar
  86. Xu Z, Lukasiewicz T, Chen C, Miao Y, XiangwuMeng (2017) Tag-aware personalized recommendation using a hybrid deep model. In: Proceedings of the twenty-sixth international joint conference on artificial intelligence, IJCAI-17, pp 3196–3202,
  87. Yang B, Lei Y, Liu J, Li W (2017) Social collaborative filtering by trust. IEEE Trans Pattern Anal Mach Intell 39(8):1633–1647Google Scholar
  88. Yang R, Hu W, Qu Y (2013) Using semantic technology to improve recommender systems based on slope one. Semantic web and web science. Springer, New York, pp 11–23Google Scholar
  89. Ye M, Yin P, Lee WC, Lee DL (2011) Exploiting geographical influence for collaborative point-of-interest recommendation. In: Proceedings of the 34th international ACM SIGIR conference on research and development in information retrieval, ACM, New York, NY, USA, SIGIR’11, pp 325–334,
  90. Zafarani R, Liu H (2013) Connecting users across social media sites: a behavioral-modeling approach. In: Proceedings of the 19th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, pp 41–49Google Scholar
  91. Zhang C, Yu L, Wang Y, Shah C, Zhang X (2017a) Collaborative user network embedding for social recommender systems. In: Proceedings of the 2017 SIAM international conference on data mining, pp 381–389,
  92. Zhang J, Tang J, Liang B, Yang Z, Wang S, Zuo J, Li J (2008) Recommendation over a heterogeneous social network. In: 2008 The ninth international conference on web-age information management, IEEE, pp 309–316,
  93. Zhang Y, Tu Z, Wang Q (2017b) TempoRec: temporal-topic based recommender for social network services. Mobile Networks Appl 22(6):1182–1191. Google Scholar
  94. Zhao L, Pan SJ, Xiang EW, Zhong E, Lu Z, Yang Q (2013) Active transfer learning for cross-system recommendation. In: Proceedings of the twenty-seventh AAAI conference on artificial intelligence, AAAI Press, AAAI’13, pp 1205–1211Google Scholar
  95. Zhao WX, Li S, He Y, Wang L, Wen JR, Li X (2016) Exploring demographic information in social media for product recommendation. Knowl Inform Syst 49(1):61–89. Google Scholar
  96. Zheng N, Li Q (2011) A recommender system based on tag and time information for social tagging systems. Expert Syst Appl 38(4):4575–4587Google Scholar
  97. Zhou J, Tang M, Tian Y, Al-Dhelaan A, Al-Rodhaan M, Lee S et al (2015) Social network and tag sources based augmenting collaborative recommender system. IEICE Trans Inform Syst 98(4):902–910Google Scholar

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Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringUniversity Institute of Engineering and Technology, M.D. UniversityRohtakIndia

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