A Social Network Analysis of Face Tracking in News Video

In the age of data processing, news videos are rich mines of information. After all, the news are essentially created to convey information to the public. But can we go beyond what is directly presented to us and see a wider picture? Many works already focus on what we can discover and understand from the analysis of years of news broadcasting. These analysis bring monitoring and understanding of the activity of public figures, political strategies, explanation and even prediction of critical media events. Such tools can help public figures in managing their public image, as well as support the work of journalists, social scientists and other media experts. News analysis can be also seen from the lens of complex systems, gathering many types of entities, attributes and interactions over time. As many public figures intervene in different news stories, a first interesting task is to observe the social interactions between these actors. Towards this goal, we propose to use video analysis to automatise the process of constructing social networks directly from news video archives. In this paper we are introducing a system deriving multiple social networks from face detections in news video. We present preliminary results obtained from analysis of these networks monitoring of the activity of more than a hundred public figures over a decade of the NHK news archives.

[1]  Julia Cagé,et al.  Media Competition, Information Provision and Political Participation: Evidence from French Local Newspapers and Elections, 1944-2014 , 2017, Journal of Public Economics.

[2]  Gianmarco De Francisci Morales,et al.  Says who?: automatic text-based content analysis of television news , 2013, UnstructureNLP@CIKM.

[3]  Ivan Herman,et al.  Density functions for visual attributes and effective partitioning in graph visualization , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[4]  Shin'ichi Satoh,et al.  Mining Large-Scale Broadcast Video Archives Towards Inter-video Structuring , 2004, PCM.

[5]  Olivier Buisson,et al.  Interactive components for visual exploration of multimedia archives , 2008, CIVR '08.

[6]  Nello Cristianini,et al.  Automating Quantitative Narrative Analysis of News Data , 2011, WAPA.

[7]  Mohan S. Kankanhalli,et al.  Proceedings of the 2008 international conference on Content-based image and video retrieval , 2008 .

[8]  Richard Sproat,et al.  Mining correlated bursty topic patterns from coordinated text streams , 2007, KDD '07.

[9]  James Allan,et al.  Topic detection and tracking: event-based information organization , 2002 .

[10]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[11]  James Philbin,et al.  FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Olivier Buisson,et al.  OTMedia: the French TransMedia news observatory , 2013, MM '13.

[13]  Hugues Bersini,et al.  Topology Analysis of Social Networks Extracted from Literature , 2015, PloS one.

[14]  Byoung-Tak Zhang,et al.  Social network analysis of TV drama characters via deep concept hierarchies , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[15]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[16]  Wolfgang Kienreich,et al.  Visual Analysis and Knowledge Discovery for Text , 2014, Large-Scale Data Analytics.

[17]  Stephen B. Seidman,et al.  Network structure and minimum degree , 1983 .

[18]  Robert Hazell,et al.  Assessing the performance of freedom of information , 2010, Gov. Inf. Q..

[19]  Tony Hey,et al.  The Fourth Paradigm: Data-Intensive Scientific Discovery , 2009 .

[20]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Guy Melançon,et al.  Entanglement in Multiplex Networks: Understanding Group Cohesion in Homophily Networks , 2014, Social Network Analysis.

[22]  Lada A. Adamic,et al.  The political blogosphere and the 2004 U.S. election: divided they blog , 2005, LinkKDD '05.

[23]  Kathleen M. Carley,et al.  Network text analysis of conceptual overlap in interviews, newspaper articles and keywords , 2013, Social Network Analysis and Mining.

[24]  Shin'ichi Satoh,et al.  Image Flows Visualization for Inter-media Comparison , 2014, 2014 IEEE Pacific Visualization Symposium.

[25]  Duy-Dinh Le,et al.  Face Retrieval in Large-Scale News Video Datasets , 2013, IEICE Trans. Inf. Syst..

[26]  Jianping Fan,et al.  Analyzing Large-Scale News Video Databases to Support Knowledge Visualization and Intuitive Retrieval , 2007, 2007 IEEE Symposium on Visual Analytics Science and Technology.

[27]  Matthieu Latapy,et al.  Computing maximal cliques in link streams , 2015, Theor. Comput. Sci..

[28]  Sean A. Munson,et al.  Bursting your (filter) bubble: strategies for promoting diverse exposure , 2013, CSCW '13.

[29]  Frank Nack,et al.  [Invited Paper] Explain This to Me! , 2013 .

[30]  Shin'ichi Satoh,et al.  Topic Threading for Structuring a Large-Scale News Video Archive , 2004, CIVR.

[31]  Mason A. Porter,et al.  Multilayer networks , 2013, J. Complex Networks.

[32]  D. Lazer.  Networks in Political Science: Back to the Future , 2011, PS: Political Science & Politics.