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Bibliometric Analysis and Systematic Review of Research on Expert Finding: A PRISMA-guided Approach
This study conducts a comprehensive exploration of expert retrieval using a dual approach of bibliometric analysis and systematic review, guided by the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) methodology. From 2000 to 2023, our investigation reveals a notable upward trajectory in expert locating study, focusing on 494 articles identified from Scopus using specific keywords related to Expert Finding (EF) and Expert Finding Systems (EFSs). Through bibliometric analysis, utilizing VOSviewer, we identify prominent co-author groups, highly-cited documents, and global participation, shedding light on the collaborative and internationally expansive nature of EF investigations. Keyword co- occurrence and text analysis reveal thematic clusters, signaling the evolving emphases in the field from foundational expert search tasks to considerations of platform interactions. Simultaneously, our systematic review, conducted on a subset of 51 articles using NVivo, explores domains seeking expert solutions, prevalent datasets, and common evaluation methods. This research not only synthesizes the current state of EF and EFS literature but also charts a course for future exploration, contributing to a deeper understanding of the field and guiding the trajectory of forthcoming research endeavors.
[1] Alam M., “A Systematic Qualitative Case Study: Questions, Data Collection, NVivo Analysis and Saturation,” Qualitative Research in Organizations and Management: An International Journal, vol. 16, no. 1, pp. 1-31, 2020. https://doi.org/10.1108/QROM-09-2019-1825
[2] Alarfaj F., Kruschwitz U., Hunter D., and Fox C., “Finding the Right Supervisor: Expert-Finding in a University Domain,” in Proceedings of the NAACL HLT Student Research Workshop, Montreal, pp. 1-6, 2012. https://aclanthology.org/N12-2001
[3] Albusac C., De Campos L., Fernández-Luna J., and Huete J., “PMSC-UGR: A Test Collection for Expert Recommendation Based on PubMed and Scopus,” in Proceedings of the 18th Conference of the Spanish Association for Advances in Artificial Intelligence, Granada, pp. 34-43, 2018. https://doi.org/10.1007/978-3-030-00374-6
[4] Amjad T., Daud A., and Aljohani N., “Ranking Authors in Academic Social Networks: A Survey,” Library Hi Tech, vol. 36, no. 1, pp. 97- 128, 2018. https://doi.org/10.1108/LHT-05-2017-0090
[5] Balog K. and De Rijke M., “Determining Expert Profiles (with an Application to Expert Finding),” in Proceedings of the 20th International Joint Conference on Artificial Intelligence, San Francisco, pp. 2657-2662, 2007. https://dl.acm.org/doi/10.5555/1625275.1625703
[6] Balog K., Azzopardi L., and Rijke M., “A Language Modeling Framework for Expert Finding,” Information Processing and Management, vol. 45, no. 1, pp. 1-19, 2009. DOI:10.1016/j.ipm.2008.06.003
[7] Balog K., Azzopardi L., and Rijke M., “Formal Models for Expert Finding in Enterprise Corpora,” in Proceedings of the 29thAnnual International ACM SIGIR, Seattle, pp. 43-50, 2006. https://doi.org/10.1145/1148170.1148181
[8] Balog K., Bogers T., Azzopardi L., Rijke M., and Bosch A., “Broad Expertise Retrieval in Sparse Data Environments,” in Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Amsterdam, pp. 551-558, 2007. https://doi.org/10.1145/1277741.1277836
[9] Bonchi F., Castillo C., Gionis A., and Jaimes A., “Social Network Analysis and Mining for Business Applications,” AMC Transactions on Intelligent Systems and Technology, vol. 2, no. 3, pp. 1-37, 2011. DOI:10.1145/1961189.1961194
[10] Bozzon A., Brambilla M., Ceri S., Silvestri M., and Vesci G., “Choosing the Right Crowd: Expert Finding in Social Networks,” in Proceedings of the 16th International Conference on Extending Database Technology, Genoa, pp. 637-648, 2013. https://doi.org/10.1145/2452376.2452451
[11] Cifariello P., Ferragina P., and Ponza M., “Wiser: A Semantic Approach for Expert Finding in Academia Based on Entity Linking,” Information Sciences, vol. 82, no. C, pp. 1-16, 2019. DOI:10.1016/j.is.2018.12.003
[12] Chen T. and Lee M., “Research Paper Recommender Systems on Big Scholarly Data,” in Proceedings of the International 15th Pacific Rim Knowledge Acquisition Workshop on Management and Acquisition for Intelligent Systems, Nanjing, pp. 251-260, 2018. https://link.springer.com/chapter/10.1007/978-3- 319-97289-3_20
[13] Cheng Z., Caverlee J., Barthwal H., and Bachani V., “Who is the barbecue king of texas? A Geo- Spatial Approach to Finding Local Experts on Twitter,” in Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, Queensland, pp.335-344, 2014. https://doi.org/10.1145/2600428.2609580
[14] D’Amore R., “Expertise Community Detection,” in Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Sheffie, pp. 498-499, 2004. https://doi.org/10.1145/1008992.1009089
[15] Dehghan M., Biabani M., and Abin A., “Temporal Expert Profiling: With an Application to T-Shaped Expert Finding,” Information Processing and Management, vol. 56, no. 3, pp. 1067-1079, 2019. https://doi.org/10.1016/j.ipm.2019.02.017
[16] Deng H., Han J., Lyu M., and King I., “Modeling and Exploiting Heterogeneous Bibliographic Networks for Expertise Ranking,” in Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries, Washington (DC), pp. 71-80, 2012. https://doi.org/10.1145/2232817.2232833
[17] Deng H., King I., and Lyu M., “Formal Models for Expert Finding on DBLP Bibliography Data,” in Proceedings of the 8th IEEE International Conference on Data Mining, Pisa, pp. 163-172, 2008. DOI:10.1109/ICDM.2008.29
[18] Dom B., Eiron I., Cozzi A., and Zhang Y., “Graph-based Ranking Algorithms for E-mail 672 The International Arab Journal of Information Technology, Vol. 21, No. 4, July 2024 Expertise Analysis,” in Proceedings of the 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, San Diego, pp. 42-48, 2003. https://doi.org/10.1145/882082.882093
[19] Fallahnejad Z. and Beigy H., “Attention-based Skill Translation Models for Expert Finding,” Expert Systems with Applications, vol. 193, pp. 116433, 2022. https://doi.org/10.1016/j.eswa.2021.116433
[20] Fang H. and Zhai C., “Probabilistic Models for Expert Finding,” in Proceedings of the 29th European Conference on Advances in Information Retrieval, Rome, pp. 418-430, 2007. https://link.springer.com/chapter/10.1007/978-3- 540-71496-5_38
[21] Fang Y., Si L., and Mathur A., “Discriminative Models of Integrating Document Evidence and Document-Candidate Associations for Expert Search,” in Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Geneva, pp. 683-690, 2010. https://doi.org/10.1145/1835449.1835563
[22] Fazel-Zarandi M., Devlin H., Huang Y., and Contractor N., “Expert Recommendation Based on Social Drivers, Social Network Analysis, and Semantic Data Representation,” in Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, Chicago, pp. 41-48, 2011. https://doi.org/10.1145/2039320.2039326
[23] Fu J., Li Y., Zhang Q., Wu Q., Ma R., Huang X., and Jiang Y., “Recurrent Memory Reasoning Network for Expert Finding in Community Question Answering,” in Proceedings of the 13th International Conference on Web Search and Data Mining, Houston, pp. 187-195, 2020. https://doi.org/10.1145/3336191.3371817
[24] Ghasemi N., Fatourechi R., and Momtazi S., “User Embedding for Expert Finding in Community Question Answering,” ACM Transactions on Knowledge Discovery from Data, vol. 15, no. 4, pp. 1-16, 2021. DOI:10.1145/3441302
[25] Hechler E., Weihrauch M., and Wu Y., Data Fabric and Data Mesh Approaches with AI, Apress, 2023. https://doi.org/10.1007/978-1- 4842-9253-2_8
[26] Husain O., Salim N., Alias R., Abdelsalam S., and Hassan A., “Expert Finding Systems: A Systematic Review,” Applied Sciences, vol. 9, no. 20, 2019. https://doi.org/10.3390/app9204250
[27] Kang Y., Du H., Forkan A., Jayaraman P., Aryani A., and Sellis T., “ExpFinder: A Hybrid Model for Expert Finding From Text-based Expertise Data,” Expert Systems with Applications, vol. 211, pp. 118691, 2023. https://doi.org/10.1016/j.eswa.2022.118691
[28] Karimzadehgan M., White R., and Richardson M., “Enhancing Expert Finding Using Organizational Hierarchies,” Advances in Information Retrieva 31st European Conference on IR Research, Toulouse, pp. 177-188, 2009. https://link.springer.com/chapter/10.1007/978-3- 642-00958-7_18
[29] Klamma R., Cuong P., and Cao Y., “You never Walk Alone: Recommending Academic Events Based on Social Network Analysis,” in Proceedings of the 1st International Conference in Complex Sciences, Shanghai, pp. 657-670, 2009. https://doi.org/10.1007/978-3-642-02466-5_64
[30] Lin S., Hong W., Wang D., and Li T., “A Survey on Expert Finding Techniques,” Journal of Intelligent Information Systems, vol. 49, no. 2, pp. 255-279, 2017. https://doi.org/10.1007/s10844- 016-0440-5
[31] Liu D., Chen Y., Kao W., and Wang H., “Integrating Expert Profile, Reputation and Link Analysis for Expert Finding in Question- Answering Websites,” Information Processing and Management, vol. 49, no. 1, pp. 312-329, 2013. DOI:10.1016/j.ipm.2012.07.002
[32] Liu X., Croft W., and Koll M., “Finding Experts in Community-based Question-Answering Services,” in Proceedings of the 14th ACM International Conference on Information and Knowledge Management, Bremen, pp 315-316, 2005. https://doi.org/10.1145/1099554.1099644
[33] Liu X., Wang G., Johri A., Zhou M., and Fan W., “Harnessing Global Expertise: A Comparative Study of Expertise Profiling Methods for Online Communities,” Information Systems Frontiers, vol. 16, no. 4, pp. 715-727, 2014. DOI:10.1007/s10796-012-9385-6
[34] Liu Y., Tang W., Liu Z., Ding L., and Tang A., “High-Quality Domain Expert Finding Method in CQA Based on Multi-Granularity Semantic Analysis and Interest Drift,” Information Sciences, vol. 596, no. C, pp. 395-413, 2022. DOI:10.1016/j.ins.2022.02.039
[35] Macdonald C. and Ounis I., “Voting for Candidates: Adapting Data Fusion techniques for an Expert Search Task,” in Proceedings of the 15th ACM international Conference on Information and Knowledge Management, Arlington, pp 387- 396, 2006. https://doi.org/10.1145/1183614.1183671
[36] Macdonald C. and Ounis I., “Voting Techniques for Expert Search,” Knowledge and Information Systems, vol. 16, no. 3, pp. 259-280, 2008. DOI:10.1007/s10115-007-0105-3
[37] Mangaravite V., Santos R., Ribeiro I., Gonçalves M., and Laender A., “The LExR Collection for Expertise Retrieval in Academia,” in Proceedings Bibliometric Analysis and Systematic Review of Research on Expert Finding: A PRISMA ... 673 of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, Pisa, pp. 721-724, 2016. https://dl.acm.org/doi/10.1145/2911451.2914678
[38] Nawaz S., Zai A., Imtiaz S., and Ashraf H., “Systematic Literature Review: Causes of Rework in GSD,” The International Arab Journal of Information Technology, vol. 19, no. 1, pp. 97- 109, 2022. DOI:10.34028/iajit/19/1/12
[39] Nobari A., Gharebagh S., and Neshati M., “Skill Translation Models in Expert Finding,” in Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Shinjuku, pp. 1057-1060, 2017. https://doi.org/10.1145/3077136.3080719
[40] Nobari A., Neshati M., and Gharebagh S., “Quality-Aware Skill Translation Models for Expert Finding on StackOverflow,” Information Systems, vol. 87, pp. 101413, 2020. https://doi.org/10.1016/j.is.2019.07.003
[41] O’Neill M., Booth S., and Lamb J., “Using NVivo™ for Literature Reviews: The Eight Step Pedagogy (N7+1),” The Qualitative Report, vol. 23, no. 13, pp. 21-39, 2018. https://doi.org/10.46743/2160-3715/2018.3030
[42] Peng Q., Liu H., Wang Y., Xu H., Jiao P., Shao M., and Wang W., “Towards a Multi-View Attentive Matching for Personalized Expert Finding,” in Proceedings of the ACM Web Conference, Lyon, pp. 2131-2140, 2022. https://doi.org/10.1145/3485447.3512086
[43] Rafiei M. and Kardan A., “A Novel Method for Expert Finding in Online Communities Based on Concept Map and PageRank,” Human-Centric Computing and Information Sciences, vol. 5, no. 1, pp. 10, 2015. DOI:10.1186/s13673-015-0030-5
[44] Serdyukov P., Rode H., and Hiemstra D., “Modeling Multi-Step Relevance Propagation for Expert Finding,” in Proceedings of the 17th ACM Conference on Information and Knowledge Management, Napa Valley, pp. 1133-1142, 2008. https://doi.org/10.1145/1458082.1458232
[45] Smirnova E. and Balog K., “A User-Oriented Model for Expert Finding,” in Proceedings of the 33rd European Conference on IR Resarch, ECIR, Dublin, pp. 580-592, 2011. https://link.springer.com/chapter/10.1007/978-3- 642-20161-5_58
[46] Strukova S., Ruipérez-Valiente J., and Mármol F., “Towards the Identification of Experts in Informal Learning Portals at Scale,” in Proceedings of the 10th ACM Conference on Learning @ Scale, Copenhagen, pp. 316-32, 2023. https://doi.org/10.1145/3573051.3596179
[47] Sun J., Xu W., Ma J., and Sun J., “Leverage RAF to Find Domain Experts on Research Social Network Services: A Big Data Analytics Methodology with MapReduce Framework,” International Journal of Production Economics, vol. 165, pp. 185-193, 2015. https://doi.org/10.1016/j.ijpe.2014.12.038
[48] Tung Y., Tseng S., Weng J., Lee T., Liao A., and Tsai W., “A Rule-based CBR Approach for Expert Finding and Problem Diagnosis,” Expert Systems with Applications, vol. 37, no. 3, pp. 2427-2438, 2010. https://doi.org/10.1016/j.eswa.2009.07.037
[49] Tran Q. and Huang D., “Using PLS-SEM to Analyze Challenges Hindering Success of Green Building Projects in Vietnam,” Journal of Economics and Development, vol. 24, no. 1, pp. 47-64, 2022. DOI:10.1108/JED-04-2020-0033
[50] Van Eck N. and Waltman L., “Accuracy of Citation Data in Web of Science and Scopus,” arXiv Preprint, vol. abs/1906.07011, pp. 1-6, 2019. https://arxiv.org/pdf/1906.07011
[51] Van Eck N. and Waltman L., “Software Survey: VOSviewer, a Computer Program for Bibliometric Mapping,” Scientometrics, vol. 84, no. 2, pp. 523-538, 2010. https://link.springer.com/article/10.1007/s11192- 009-0146-3
[52] Van Eck N. and Waltman L., “VOSviewer Manual,” Univeristeit Leiden, pp. 1-54, 2022. https://www.vosviewer.com/documentation/Man ual_VOSviewer_1.6.18.pdf
[53] Wang C., Han J., Jia Y., Tang J., Zhang D., Yu Y., and Guo J., “Mining Advisor-Advisee Relationships from Research Publication Networks,” in Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington (DC), pp. 203-212, 2010. https://doi.org/10.1145/1835804.1835833
[54] Wang G., Jiao J., Abrahams A., Fan W., and Zhang Z., “ExpertRank: A Topic-Aware Expert Finding Algorithm for Online Knowledge Communities,” Decision Support Systems, vol. 54, no. 3, pp. 1442-1451, 2013. https://doi.org/10.1016/j.dss.2012.12.020
[55] Wei W., Cong G., Miao C., Zhu F., and Li G., “Learning to Find Topic Experts in Twitter via Different Relations,” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 7, pp. 1764-1778, 2016. DOI:10.1109/TKDE.2016.2539166
[56] Wu D., Fan S., and Yuan F., “Research on Pathways of Expert Finding on Academic Social Networking Sites,” Information Processing and Management, vol. 58, no. 2, pp. 102475, 2021. https://doi.org/10.1016/j.ipm.2020.102475
[57] Yang Z., Liu Q., Sun B., and Zhao X., “Expert Recommendation in Community Question Answering: A Review and Future Direction,” International Journal of Crowd Science, vol. 3, no. 3, pp. 348-372, 2019. 674 The International Arab Journal of Information Technology, Vol. 21, No. 4, July 2024 https://doi.org/10.1108/IJCS-03-2019-0011
[58] Yimam D. and Kobsa A., “DEMOIR: A Hybrid Architecture for Expertise Modeling and Recommender Systems,” in Proceedings IEEE 9th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, Gaithersburg, pp. 67-74, 2000. DOI:10.1109/ENABL.2000.883706
[59] Yuan S., Zhang Y., Tang J., Hall W., and Cabota J., “Expert Finding in Community Question Answering: A Review,” Artificial Intelligence Review, vol. 53, no. 2, pp. 843-874, 2020. DOI:10.1007/s10462-018-09680-6
[60] Zhao Z., Zhang L., He X., and Ng W., “Expert Finding for Question Answering via Graph Regularized Matrix Completion,” IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 4, pp. 993-1004, 2015. DOI:10.1109/TKDE.2014.2356461
[61] Zhou G., Lai S., Liu K., and Zhao J., “Topic- Sensitive Probabilistic Model for Expert Finding in Question Answer Communities,” in Proceedings of the 21st ACM International Conference on Information and Knowledge Management, Maui, pp. 1662-1666, 2012. https://doi.org/10.1145/2396761.2398493
[62] Zhu H., Cao H., Xiong H., Chen E., and Tian J., “Towards Expert Finding by Leveraging Relevant Categories in Authority Ranking,” in Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Glasgow, pp. 2221-2224, 2011. https://doi.org/10.1145/2063576.2063931
[63] Zhu H., Chen E., Xiong H., Cao H., and Tian J., “Ranking User Authority with Relevant Knowledge Categories for Expert Finding,” World Wide Web, vol. 17, no. 5, pp. 1081-1107, 2014. DOI: 10.1007/s11280-013-0217-5