Abstract
The ability to quickly extract relevant knowledge from large-scale information repositories like the World Wide Web, scholarly publication databases or Online Social Networks has become crucial to our information society. Apart from the technical issues involved in the storage, processing and retrieval of huge amounts of data, the design of automated mechanisms which rank and filter information based on their relevance (i) in a given context, and (ii) to a particular user has become a major challenge. In this chapter we argue that, due to the fact that information systems are increasingly interwoven with the social systems into which they are embedded, the ranking and filtering of information is effectively a socio-technical problem. Drawing from recent developments in the context of social information systems, we highlight a number of research challenges which we argue should become an integral part of a social informatics research agenda. We further review promising research approaches that can give rise to a systems design of information systems that addresses both its technical and social dimension in an integrated way.
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References
Anvik J (2006) Automating bug report assignment. In: Proceedings of the 28th international conference on software engineering, ICSE ’06, Shanghai. ACM, New York, pp 937–940. 10.1145/1134285.1134457. http://doi.acm.org/10.1145/1134285.1134457
Bakshy E, Rosenn I, Marlow C, Adamic L (2012) The role of social networks in information diffusion. In: Proceedings of the 21st international conference on world wide web, Lyon. ACM, pp 519–528
Berners-Lee T, Groff JF (1992) Www. SIGBIO Newsl 12(3):37–40. 10.1145/147126.147133. http://doi.acm.org/10.1145/147126.147133
Bettenburg N, Just S, Schröter A, Weiss C, Premraj R, Zimmermann T (2008) What makes a good bug report? In: Proceedings of the 16th ACM SIGSOFT international symposium on foundations of software engineering, SIGSOFT ’08/FSE-16, Atlanta. ACM, New York, pp 308–318. 10.1145/1453101.1453146. http://doi.acm.org/10.1145/1453101.1453146
Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput Netw ISDN Syst 30(1–7):107–117. 10.1016/S0169-7552(98)00110-X. http://linkinghub.elsevier.com/retrieve/pii/S016975529800110X
Bughin J, Corb L, Manyika J, Nottebohm O, Chui M, de Muller Barbat B, Said R (2011) The impact of internet technologies: search. McKinsey&Company, High Tech Practice
Cubranic D, Murphy GC (2004) Automatic bug triage using text categorization. In: Maurer F, Ruhe G (eds) SEKE, Banff, pp 92–97
Frisse M (1988) Searching for information in a hypertext medical handbook. Commun ACM 31(7):880–886
Gao J, Buldyrev SV, Stanley HE, Havlin S (2012) Networks formed from interdependent networks. Nat Phys 8(1):40–48
Garcia D, Schweitzer F (2012) Modeling online collective emotions. In: Proceedings of the 2012 workshop on data-driven user behavioral modelling and mining from social media-DUBMMSM ’12, CIKM2012, Maui. ACM, New York, p 37. 10.1145/2390131.2390147. http://dl.acm.org/citation.cfm?id=2390131.2390147
Goldman R, Shivakumar N, Venkatasubramanian S, Garcia-Molina H (1998) Proximity search in databases. In: Proceedings of the 24th international conference on very large data bases, VLDB ’98, New York. Morgan Kaufmann Publishers, San Francisco, pp 26–37. http://dl.acm.org/citation.cfm?id=645924.671346
Granovetter M (1973) The strength of weak ties. Am J Sociol 78(6):l
Halu A, Mondragón RJ, Panzarasa P, Bianconi G (2013) Multiplex pagerank. PLoS ONE 8(10):e78,293. 10.1371/journal.pone.0078293. http://dx.doi.org/10.1371%2Fjournal.pone.0078293
Hannak A, Sapiezynski P, Molavi Kakhki A, Krishnamurthy B, Lazer D, Mislove A, Wilson C (2013) Measuring personalization of web search. In: Proceedings of the 22nd international conference on world wide web, Rio de Janeiro. International World Wide Web Conferences Steering Committee, pp 527–538
Haveliwala T, Kamvar S, Jeh G (2003) An analytical comparison of approaches to personalizing pagerank. Technical report 2003–35, Stanford InfoLab. http://ilpubs.stanford.edu:8090/596/
Holme P, Saramäki J (2012) Temporal networks. Phys Rep 519(3):97–125
Introna L, Nissenbaum H (2000) The politics of search engines. IEEE Comput 54–62. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=816269
Jeh G, Widom J (2003) Scaling personalized web search. In: Proceedings of the 12th international conference on world wide web, WWW ’03, Budapest. ACM, New York, pp 271–279. 10.1145/775152.775191. http://doi.acm.org/10.1145/775152.775191
Kleinberg J (1999) Authoritative sources in a hyperlinked environment. J ACM (JACM) 46:604–632. http://dl.acm.org/citation.cfm?id=324140
Kraemer F, Overveld K, Peterson M (2010) Is there an ethics of algorithms? Ethics Inf Technol 13(3):251–260. 10.1007/s10676-010-9233-7. http://link.springer.com/10.1007/s10676-010-9233-7
Kwak H, Lee C, Park H, Moon S (2010) What is Twitter, a social network or a news media? In: Proceedings of the 19th international conference on world wide web, Raleigh. ACM, pp 591–600
Lerman K, Ghosh R (2010) Information contagion: an empirical study of the spread of news on Digg and Twitter social networks. ICWSM 10:90–97
Liben-Nowell D, Kleinberg J (2003) The link prediction problem for social networks. In: Proceedings of the twelfth international conference on information and knowledge management, CIKM ’03, New Orleans. ACM, New York, pp 556–559. 10.1145/956863.956972. http://doi.acm.org/10.1145/956863.956972
Mavrodiev P, Tessone CJ, Schweitzer F (2012) Effects of social influence on the wisdom of crowds. CoRR abs/1204.3463
Naaman M, Boase J, Lai, CH (2010) Is it really about me?: message content in social awareness streams. In: Proceedings of the 2010 ACM conference on computer supported cooperative work, Savannah. ACM, pp 189–192
Newman MEJ (2010) Networks: an introduction. Oxford University Press, Oxford/New York. 10.1093/acprof:oso/9780199206650.001.0001. http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199206650.001.0001/acprof-9780199206650
Page L, Brin S, Motwani R, Winograd T (1999) The PageRank citation ranking: bringing order to the web. Technical report, Stanford InfoLab. http://ilpubs.stanford.edu:8090/422
Pariser E (2011) The filter bubble: what the Internet is hiding from you. Penguin, New York
Parunak HVD (2011) Swarming on symbolic structures: guiding self-organizing search with domain knowledge. In: Eighth international conference on information technology: new generations, ITNG 2011, Las Vegas, 11–13 Apr 2011, pp 896–901
Parunak HVD, Downs E, Yinger A (2011) Socially-constrained exogenously-driven opinion dynamics: explorations with a multi-agent model. In: SASO, Ann Arbor. IEEE, pp 158–167
Pfitzner R, Garas A (2012) Emotional divergence influences information spreading in Twitter. In: AAAI ICWSM 2012, pp 2–5
Pfitzner R, Scholtes I, Garas A, Tessone CJ, Schweitzer F (2013) Betweenness preference: quantifying correlations in the topological dynamics of temporal networks. Phys Rev Lett 110(19):198,701. 10.1103/PhysRevLett.110.198701. http://prl.aps.org/abstract/PRL/v110/i19/e198701
Rosvall M, Esquivel AV, Lancichinetti A, West JD, Lambiotte R (2013) Networks with memory. arXiv preprint, arXiv:1305.4807
Sarigöl E, Pfitzner R, Scholtes I, Garas A, Schweitzer F (2014) Predicting scientific success based on coauthorship networks. Working paper
Scheitzer F (2003) Brownian agents and active particles. Collective dynamics in the natural and social sciences. Springer series in synergetics. Springer, Berlin
Scholtes I, Wider N, Pfitzner R, Garas A, Tessone CJ, Schweitzer F (2013) Slow-down vs. speed-up of diffusion in non-markovian temporal networks. arXiv preprint. http://arxiv.org/abs/1307.4030
Šuvakov M, Garcia D, Schweitzer F, Tadić B (2012) Agent-based simulations of emotion spreading in online social networks. ArXiv e-prints
Tomforde S, Hähner J, Seebach H, Reif W, Sick B, Wacker A, Scholtes I (2014) Engineering and mastering interwoven systems. In: Proceedings of the 2nd international workshop on self-optimisation in organic and autonomic computing systems (SAOS 2014), Lübeck
Walter FE, Battiston S, Schweitzer F (2009) Personalised and dynamic trust in social networks. In: Proceedings of the third ACM conference on Recommender systems – RecSys ’09, New York. ACM, New York, pp 197–204. 10.1145/1639714.1639747
Zanetti MS, Scholtes I, Tessone CJ, Schweitzer F (2013) Categorizing bugs with social networks: a case study on four open source software communities. In: Proceedings of the 35th international conference on software engineering, ICSE ’13, San Francisco, 18–26 May 2013, pp 1032–1041
Zwass V (2014) In: Encyclopaedia britannica http://www.britannica.com/EBchecked/topic/287895/information-system. Retrieved 11 Feb 2014
Acknowledgements
IS and FS acknowledge support by the Swiss National Foundation, grant no. CR31I1_140644/1. We further acknowledge support by COST action TD1210: Analyzing the dynamics of information and knowledge landscapes.
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Scholtes, I., Pfitzner, R., Schweitzer, F. (2014). The Social Dimension of Information Ranking: A Discussion of Research Challenges and Approaches. In: Zweig, K., Neuser, W., Pipek, V., Rohde, M., Scholtes, I. (eds) Socioinformatics - The Social Impact of Interactions between Humans and IT. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-09378-9_4
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