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Collective Intelligence: Overview

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Synonyms

Emergent semantics; Social media analysis

Glossary

Community detection:

A class of network analysis algorithms that identify groups of nodes that are densely connected

Data mining:

Extracting implicit information from a domain

Graph:

A set of nodes and edges connecting the nodes

Multimodal:

A kind of analysis involving more than one media or metadata types (e.g., text, image, geolocation)

Network:

A graph that assigns some semantics to the nodes and kind of interaction for the links

SNA:

Social network analysis is the study of social network characteristics and dynamics

UGC:

User-generated multimedia content (image, text) that is created/captured by casual users and shared online

Definition

Recent advances of Web technologies have effectively turned ordinary people into active members of the Web: casual users act as co-developers, and their interactions and collaborations with each other have added a new social dimension on Web data. For example, Wikipedia (http://www.wikipedia.org...

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References

  • Ahmed M, Spagna S, Huici F, Niccolini F (2013) A peek into the future: predicting the evolution of popularity in user generated content. In: Proceedings of the 6th ACM international conference web search and data mining, pp 607–616

    Google Scholar 

  • Aiello LM, Petkos G, Martin C, Corney D, Papadopoulos S, Skraba R, Göker A, Kompatsiaris I, Jaimes A (2013) Sensing trending topics in Twitter. Trans Multimed 15(6):1268–1282. https://doi.org/10.1109/TMM.2013.2265080

    Article  Google Scholar 

  • Arapakis I, Barla Cambazoglu B, Lalmas M (2014) On the feasibility of predicting news popularity at cold start. In Prpc. 6th international conference, SocInfo 2014, Barcelona, Spain, 11–13 November 2014, pp 290–299

    Google Scholar 

  • Au Yeung CM, Gibbins N, Shadbolt N (2009) Contextualising tags in collaborative tagging systems. In: HT ‘09: proceedings of 20th ACM conference on hypertext and hypermedia, pp 251–260

    Google Scholar 

  • Becker H, Naaman M, Gravano L (2010) Learning similarity metrics for event identification in social media. In: Proceedings of the third ACM international conference on web search and data mining, WSDM ‘10. ACM, New York, pp 291–300

    Google Scholar 

  • Cai X, Nie F, Huang H, Kamangar F (2011) Heterogeneous image feature integration via multi-modal spectral clustering. In: 2011 I.E. conference on computer vision and pattern recognition (CVPR), pp 1977–1984. https://doi.org/10.1109/CVPR.2011.5995740

  • Chiarandini L, Grabowicz PA, Trevisiol M, Jaimes A (2013) Leveraging browsing patterns for topic discovery and photostream recommendation. In ICWSM‘13: 7th international AAAI conference on weblogs and social media, Boston, USA

    Google Scholar 

  • De Choudhury M, Feldman M, Amer S, Golbandi N, Lempel R, Yu C (2011) Automatic construction of travel itineraries using social breadcrumbs. Proceedings of 21st ACM conference on hypertext and hypermedia, pp 35–44

    Google Scholar 

  • Gemmell J, Shepitsen A, Mobasher B, Burke R (2008) Personalizing navigation in folksonomies using hierarchical tag clustering. In: DaWaK ‘08: proceedings of 10th international conference on data warehousing and knowledge discovery, pp 196–205

    Google Scholar 

  • Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L (2009) Detecting influenza epidemics using search engine query data. Nature 457:1012–1014

    Article  Google Scholar 

  • Girardin F, Calabrese F, Dal Fiore F, Ratti C, Blat J (2008) Digital footprinting: uncovering tourists with user-generated content. IEEE Pervasive Comput 7(4):36–43

    Article  Google Scholar 

  • Henrich A, Lüdecke V (2008) Determining geographic representations for arbitrary concepts at query time. In: Proceedings of first international workshop on location and the web, pp 17–24

    Google Scholar 

  • Hinze A, Voisard A (2003) Location and time-based information delivery in tourism, advances in spatial and temporal databases. Lect Notes Comput Sci 2750:489–507

    Article  Google Scholar 

  • Jeon J, Lavrenko V, Manmatha R (2003) Automatic image annotation and retrieval using cross-media relevance models. Proceedings of 26th annual international ACM SIGIR conference on research and development in information retrieval, pp 119–126

    Google Scholar 

  • Jin X, Gallagher A, Cao L, Luo J, Han J (2010) The wisdom of social multimedia: using Flickr for prediction and forecast. MM ‘10 proceedings of international conference on multimedia, pp 1235–1244

    Google Scholar 

  • Kalantidis Y, Tolias G, Avrithis Y, Phinikettos M, Spyrou E, Mylonas P, Kollias S (2011) VIRaL: visual image retrieval and localization. Multimed Tools Appl 51(2):555–592

    Article  Google Scholar 

  • Kendall T, Zhou D (2009) Leveraging information in a social network for inferential targeting of advertisements, US Patent App. 12/419,958

    Google Scholar 

  • Kennedy LS, Naaman M, Ahern S, Nair R, Rattenbury T (2007) How Flickr helps us make sense of the world: context and content in community-contributed media collections. In: Proceedings of the ACM multimedia ‘07, pp 631–640

    Google Scholar 

  • Li J, Wang JZ (2003) Automatic linguistic indexing of pictures by a statistical modeling approach. IEEE Trans Pattern Anal Mach Intell 25:1075–1088

    Article  Google Scholar 

  • Lin YR, Candan KS, Sundaram H, Xie L (2011) Scent: scalable compressed monitoring of evolving multi-relational social networks. ACM Trans Multimedia Comput Commun App 2(3):1–25

    Google Scholar 

  • Liu D, Hua XS, Wang M, Zhang HJ (2010) Retagging social images based on visual and semantic consistency. In: Proceedings of 19th international conference on world wide web, WWW’10, pp 1149–1150

    Google Scholar 

  • Macskassy SA, Provost F (2007) Classification in networked data: a toolkit and a univariate case study. J Mach Learn Res 8:935–983

    Google Scholar 

  • Martin-Borregon D, Aiello LM, Grabowicz P, Jaimes A, Baeza-Yates R (2014) Characterization of online groups along space, time, and social dimensions. EPJ Data Sci 2014:8

    Article  Google Scholar 

  • Nikolopoulos ., Giannakidou E, Kompatsiaris I, Patras I, Vakali A (2011, in press) Combining multi-modal features for social media analysis. In: Hoi S, Luo J, Boll S, Xu D, Jin R, King I (eds) Social media modeling and computing. Springer, Berlin, pp 71–96

    Chapter  Google Scholar 

  • Papadopoulos S, Zigkolis C, Kompatsiaris Y, Vakali A (2011a) Cluster-based landmark and event detection on tagged photo collections. IEEE Multimed 18(1):52–63

    Article  Google Scholar 

  • Papadopoulos S, Zigkolis C, Kapiris S, Kompatsiaris Y, Vakali A (2011b) City exploration by use of spatio-temporal analysis and clustering of user contributed photos. Demo paper in ACM international conference on multimedia retrieval (ICMR), pp 65:1–65:2

    Google Scholar 

  • Petkos G, Schinas M, Papadopoulos S, Kompatsiaris I (2016) Graph-based multimodal clustering for social multimedia. Multimed Tools Appl. https://doi.org/10.1007/s11042-016-3378-2

  • Quack T, Leibe B, Van Gool L (2008) World-scale mining of objects and events from community photo collections. In: Proceedings of the international conference on content-based image and video retrieval, pp 47–56

    Google Scholar 

  • Quercia D, Schifanella R, Aiello LM (2014) The shortest path to happiness: recommending beautiful, quiet and happy routes in the city. In: Proceedings of the 25th ACM conference on hypertext and social media (HT ‘14). ACM, New York, NY, USA, pp 116–125. https://doi.org/10.1145/2631775.2631799

  • Sakaki T, Okazaki M, Matsuo Y (2010) Earthquake shakes Twitter users: real-time event detection by social sensors. In: World wide web conference, pp 851–860

    Google Scholar 

  • Schifanella R, Barrat A, Cattuto C, Markines B, Menczer F (2010) Folks in folksonomies: social link prediction from shared metadata. In: WSDM ‘10: Proceedings of the 3rd ACM international conference on web search and data mining, pp 271–280

    Google Scholar 

  • Signorini A (2011) Swine Flu monitoring using Twitter. http://compepi.cs.uiowa.edu/ alessio/twitter − monitor − swine − flu/. Accessed 25 Oct 2011

  • Specia L, Motta E (2007) Integrating folksonomies with the semantic web. In: ESWC ‘07: proceedings of 4th European conference on The semantic web, pp 624–639

    Google Scholar 

  • Tang L, Liu H (2011) Leveraging social media networks for classification. Data Min Knowl Disc 23:447–478

    Article  MathSciNet  MATH  Google Scholar 

  • Tsakalidis A, Papadopoulos S, Kompatsiaris I, (2014) An ensemble model for cross-domain polarity classification on Twitter. In: Proceedings of web information systems engineering – WISE 2014, Springer, pp. 168–177

    Chapter  Google Scholar 

  • Wen Z, Lin CY (2010) On the quality of inferring interests from social neighbors. In: Proceedings of 16th ACM SIGKDD international conference on knowledge discovery and data mining (KDD’10), pp 373–382

    Google Scholar 

  • Wu X, Ngo CW, Hauptmann AG, Tan HK (2009) Real-time near-duplicate elimination for web video search with content and context. Multimed IEEE Trans 11(2):196–207

    Article  Google Scholar 

  • Yang YH, Wu PT, Lee CW, Lin KH, Hsu WH, Chen HH (2008) ContextSeer: context search and recommendation at query time for shared consumer photos. In: Proceedings of the 16th ACM international conference on multimedia (MM ‘08), pp 199–208

    Google Scholar 

  • Zhang T, Ramakrishnan R, Livny M (1996) BIRCH: an efficient data clustering method for very large databases. SIGMOD Rec 25(2):103–114

    Article  Google Scholar 

  • Zhou D, Bousquet O, Lal TN, Weston J, Schölkopf B (2004) Learning with local and global consistency. Adv NIPS 16:321–328

    Google Scholar 

  • Zigkolis C, Papadopoulos S, Filippou G et al (2014) Multimed Tools Appl 70:89. https://doi.org/10.1007/s11042-012-1154-5

    Article  Google Scholar 

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Acknowledgments

The work presented in this article was supported by the European Commission under contracts FP7-215453 WeKnowIt and FP7-287975 SocialSensor.

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Correspondence to Sotiris Diplaris .

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Kompatsiaris, I., Diplaris, S., Papadopoulos, S. (2018). Collective Intelligence: Overview. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_106

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