Home » Articole » EN » Society » Social Networks » Social Media – Research Challenges

Social Media – Research Challenges

Social Media

See bellow selected open research challenges that are currently being investigated by the research community. These are only few of the dozens of research challenges that the research community faces towards the quest for a ubiquitous, intuitive and secure social web.

Avoiding fragmentation of the social graph through open cross-platform interactions

A major hindrance to exploitation of social network data is the fragmentation of the population of social network users into numerous proprietary and closed social networks. This issue is compounded by the fact that each new game or media application tends to build its own social network around it rather than building upon the rich data available about existing social relationships. Also applications are oft en restricted to execute within the confines of specific social network platform. A major research challenge, therefore, that would benefi t the exploitation of social network graphs for future media networking, is in finding solutions to open up social network platforms to allow cross-platform information exchange and usage. Of course, reliable mechanisms to preserve privacy are an essential prerequisite.

Communities discovery and analysis in large scale online and offline social networks

As social networks will continue to evolve, discovering communities and constructing specific social graphs from large scale social networks will continue to be a dynamic research challenge [15].

Security by means of Social Networks Analysis

Th e information extracted from Social Networks proved to be a useful tool towards security. One example of an application related to security is the Analysis of terrorism [20], as for instance, the Analysis of the 9-11 Terrorist Network [21] . This study was done by gathering public information from major newspapers on the WWW and analysed it be means of Social networks. A major research challenge on social network analysis is also cyber surveillance for unlawful activities for critical infrastructure protection [21].

Social and Ethical Issues in a Networked World

As in every small or large community, online social communities face also critical social and ethical issues that need special care and delicate handling. Sharing of personal information, protection of child exploitation and many other problems have to be studied and answered appropriately [19].

Searching blogs, tweets, and other social media

Searching in blogs, tweets and other social media is still an open issue since posts are very small in size but frequent, with little contextual information and sometimes extremely temporal [4]. Moreover, diff erent users have diff erent needs when it comes to the consumption of social media. Real time search has to balance between quality, authority, relevance and timeliness of the content.

Human-powered community question answering and expert finding.

Human powered (aka crowdsourcing) systems gave promising solutions to problems that were unsolved for years. Th e research community should continue working on leveraging human intelligence to solve critical problems and answer questions that otherwise would be impossible to answer automatically [5][6]. Social networks contain immense knowledge through their users. However, it is not trivial to fi nd the one that has the knowledge and is also available to share it [7].

Traffic prediction for dimensioning media applications

Investigation of how to exploit knowledge of social network relationships to predict how media consumption may be correlated between groups of users. Th is information can be used to dimension media servers and network resources to avoid congestion and improve QoE.

Social, mobile, pervasive content sharing and live media distribution

Since users act as prosumers, content sharing and distribution needs will continue to increase. Mobile phones, digital cameras and other pervasive devices produce huge amounts of data that users want to distribute if possible in real time [13] [14].

Spam, opinions and adversarial interactions in social media

Spam detection and advertisement detection are research challenges that need extra attention from the research community. Since users and data production increase, spam (irrelevant in-formation) and advertisements will continue growing [1].

In addition, the importance of social networks to infl uence the opinions of the users should be protected with the adequate mechanism to avoid biased and fake opinions due to the relevance to the businesses.

Personalisation for social interaction

In order to improve social interaction and enhance social inclusion, personalization engines that locate peers with possibly common likes, dislikes or developing trends should be engineered. Towards more effi cient search engines that will be able to serve the users only with relevant content, personalisation algorithms have to be studied in a greater extent.

Dynamics and evolution patterns of social networks, trend prediction

Research in dynamics and trends in social networks will provide more valuable tools for information extraction that may be used for content management and delivery, epidemic predictions or recommender systems[2][3].

Information diff usion in Social Networks

Research in Information diff usion is more than ever needed since the domination of social networks as a communication platform [16][17][18].

Use of Social Networks for business and marketing

Social networking introduced novel collaboration paradigms between network users and serious study is conducted on the use of such platforms for internal business purposes [11]. However, one of most prominent research challenges is how to use social networking for external communications, customer support and of course targeted marketing [12].

Social gaming and social television

Research is needed on better mass feedback mechanisms for both social gaming and social television. For social gaming as “serious game” is a research challenge.

Immersive Social Networks

Immersive social networks will be the future web platforms for social interaction, communication and infotainment. Immersion will provide an intuitive environment and enhance user experience in order to let the users socialize and interact in a more natural way.

References

[1] Benjamin Markines, Ciro Cattuto, and Filippo Menczer; “Social spam detection”. In Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb ‘09), Dennis Fetterly and Zolt\&\#225;n Gy\&\#246;ngyi (Eds.). ACM, New York, NY, USA, 41-48. DOI=10.1145/1531914.1531924 http://doi.acm.org/10.1145/1531914.1531924

[2] Takeshi Sakaki, Makoto Okazaki, and Yutaka Matsuo; “Earthquake shakes Twitter users: real-time event detection by social sensors”. In Proceedings of the 19th international conference on World wide web (WWW ‘10). ACM, New York, NY, USA, 851-860. DOI=10.1145/1772690.1772777 http://doi.acm. org/10.1145/1772690.1772777

[3] Lampos, Vasileios; Cristianini, Nello; “Tracking the fl u pandemic by monitoring the social web,” Cognitive Information Processing (CIP), 2010 2nd International Workshop on , vol., no., pp.411-416, 14-16 June 2010 doi: 10.1109/CIP.2010.5604088

[4] White, T.; Chu, W.; Salehi-Abari, A.; “Media Monitoring Using Social Networks,” Social Computing (Social-Com), 2010 IEEE Second International Conference on, vol., no., pp.661-668, 20-22 Aug. 2010 doi: 10.1109/ SocialCom.2010.102

[5] Rodrigues, E.M.; Milic-Frayling, N.; Fortuna, B.; “Social Tagging Behaviour in Community-Driven Question Answering,” Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT ‘08. IEEE/WIC/ACM International Conference on vol.1, no., pp.112-119, 9-12 Dec. 2008 doi: 10.1109/WIIAT.2008.138

[6] Li, G.; Li, H.; Ming, Z.; Hong, R.; Tang, S.; Chua, T.; “Question Answering over Community Contributed Web Video,” Multimedia, IEEE, no.99, pp.1-1, 0 doi: 10.1109/MMUL.2010.47

[7] Jian Jiao; Jun Yan; Haibei Zhao; Weiguo Fan; “ExpertRank: An Expert User Ranking Algorithm in Online Communities,” New Trends in Information and Service Science, 2009. NISS ‘09. International Conference on, vol., no., pp.674-679, June 30 2009-July 2 2009 doi: 10.1109/NISS.2009.75

[8] Walenz, B.; Gandhi, R.; Mahoney, W.; Quiming Zhu; “Exploring Social Contexts along the Time Dimension: Temporal Analysis of Named Entities,” Social Computing (SocialCom), 2010 IEEE 2nd International Conference on, vol., no., pp.508-512, 20-22 Aug. 2010 doi: 10.1109/SocialCom.2010.80

[9] Yu-Ru Lin; Sundaram, H.; De Choudhury, M.; Kelliher, A.; “Temporal patterns in social media streams: Th eme discovery and evolution using joint analysis of content and context,” Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on, vol., no., pp.1456-1459, June 28 2009-July 3 2009 doi: 10.1109/ ICME.2009.5202777

[10] Trier, M.; Bobrik, A.; “Social Search: Exploring and Searching Social Architectures in Digital Networks,” Internet Computing, IEEE , vol.13, no.2, pp.51-59, March-April 2009 doi: 10.1109/MIC.2009.44

[11] Fortino, A.; Nayak, A.; “An architecture for applying social networking to business,” Applications and Technology Conference (LISAT), 2010 Long Island Systems , vol., no., pp.1-6, 7-7 May 2010 doi: 10.1109/ LISAT.2010.5478285

[12] Yu Zhang; Zhaoqing Wang; Chaolun Xia; “Identifying Key Users for Targeted Marketing by Mining Online Social Network,” Advanced Information Networking and Applications Workshops (WAINA), 2010 IEEE 24th International Conference on , vol., no., pp.644-649, 20-23 April 2010 doi: 10.1109/WAINA.2010.137

[13] Conti, M.; Delmastro, F.; Passarella, A.; “Social-aware Content Sharing in Opportunistic Networks,” Sensor, Mesh and Ad Hoc Communications and Networks Workshops, 2009. SE-CON Workshops ‘09. 6th Annual IEEE Communications Society Conference on , vol., no., pp.1-3, 22-26 June 2009 doi: 10.1109/ SAHCNW.2009.5172964

[14] Santos, R.O.; Fabris, F.; Martinello, M.; Marcondes, C.; “JoinUs: Management of Mobile Social Networks for Pervasive Collaboration,” Sistemas Colaborativos, 2008 Simpósio Brasileiro de , vol., no., pp.224-234, 27-29 Oct. 2008. doi: 10.1109/SBSC.2008.14

[15] Prakash, B.A.; Seshadri, M.; Sridharan, A.; Machiraju, S.; Faloutsos, C.; , “EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs,” Data Mining Workshops, 2009. ICDMW ‘09. IEEE International Conference on, vol., no., pp.290-295, 6-6 Dec. 2009 doi: 10.1109/ICDMW.2009.103

[16] Bo Xu; Lu Liu; “Information diff usion through online social networks,” Emergency Management and Management Sciences (ICEMMS), 2010 IEEE International Conference on , vol., no., pp.53-56, 8-10 Aug. 2010 doi: 10.1109/ICEMMS.2010.5563505

[17] Jin-Tao Tang; Ting Wang; Ji Wang; “Measuring the infl uence of social networks on information diff usion on blogspheres,” Machine Learning and Cybernetics, 2009 International Conference on , vol.6, no., pp.3492-3498, 12-15 July 2009 doi: 10.1109/ICMLC.2009.5212771

[18] Apolloni, A.; Channakeshava, K.; Durbeck, L.; Khan, M.; Kuhlman, C.; Lewis, B.; Swarup, S.; “A Study of Information Diff usion over a Realistic Social Network Model,” Computational Science and Engineering, 2009. CSE ‘09. International Conference on , vol.4, no., pp.675-682, 29-31 Aug. 2009

[19] Garcia-Ruiz, M.A.; Martin, M.V.; Ibrahim, A.; Edwards, A.; Aquino-Santos, R.; , “Combating Child Exploitation in Second Life,” Science and Technology for Humanity (TIC-STH), 2009 IEEE Toronto International Conference, vol., no., pp.761-766, 26-27 Sept. 2009doi: 10.1109/TIC-STH.2009.5444398

[20] Uff e Kock Wiil, Jolanta Gniadek, Nasrullah Memon; Measuring Link Importance in Terrorist Networks. Social Network Analysis, 225-232. Ed. Nasrullah Memon, Reda Alhajj (Eds.): Interna-tional Conference on Advances in Social Networks Analysis and Mining, ASONAM 2010, Od-ense, Denmark, August 9-11, 2010. IEEE Computer Society 2010, ISBN 978-0-7695-4138-9

[21] Krebs Valdis. “Uncloaking Terrorist Networks.” First Monday 7, no. 4 (March2002). http://www.fi rstmonday.org/issues7 4/krebs..

[22] Vaclav Snasel, Ajith Abraham, Khalid Saeed and Hameed Al-Qaheri, A Framework for Cyber Surveillance of Unlawful Activities for Critical Infrastructure Using Computational Grids, Editors: Sixth International Conference on Information Assurance and Security (IAS), USA, IEEE, ISBN 978-1-4244-7408-0, pp. 345- 350, 2010.

© European Union

Leave a Reply

Your email address will not be published. Required fields are marked *