Keyword based searching in social networks

The main purpose of analyzing the social network data is to observe the behaviors and trends that are followed by people. How people interact with each other, what they usually share, what are their interests on social networks, so that analysts can focus new trends for the provision of those things which are of great interest for people so in this paper an easy approach of gathering and analyzing data through keyword based search in social networks is examined using NodeXL and data is gathered from twitter in which political trends have been analyzed. As a result it will be analyzed that, what people are focusing most in politics.

[1]  Bart Selman,et al.  Referral Web: combining social networks and collaborative filtering , 1997, CACM.

[2]  Matthew Richardson,et al.  Yes, there is a correlation: - from social networks to personal behavior on the web , 2008, WWW.

[3]  Gerhard Weikum,et al.  Efficient top-k querying over social-tagging networks , 2008, SIGIR '08.

[4]  Vijeth Patil,et al.  Keyword Search in Social Networks , 2012 .

[5]  Ben Shneiderman,et al.  Analyzing Social Media Networks with NodeXL: Insights from a Connected World , 2010 .

[6]  Oded Shmueli,et al.  SoQL: A Language for Querying and Creating Data in Social Networks , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[7]  Munindar P. Singh,et al.  Searching social networks , 2003, AAMAS '03.

[8]  Peter Mika,et al.  Flink: Semantic Web technology for the extraction and analysis of social networks , 2005, J. Web Semant..

[9]  Danah Boyd,et al.  Vizster: visualizing online social networks , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..

[10]  Stefan Stieglitz,et al.  Social media and political communication: a social media analytics framework , 2012, Social Network Analysis and Mining.

[11]  Claudio Gutiérrez,et al.  SNQL: A Social Networks Query and Transformation Language , 2011, AMW.

[12]  Ben Shneiderman,et al.  Analyzing Social Media Networks with NodeXL: Insights from a Connected World , 2010 .

[13]  Sara Cohen,et al.  A Social Network Database that Learns How to Answer Queries , 2013, CIDR.

[14]  Yerach Doytsher,et al.  Querying geo-social data by bridging spatial networks and social networks , 2010, LBSN '10.