@article{(Open Science Index):https://publications.waset.org/pdf/10009415,
	  title     = {Understanding the Selectional Preferences of the Twitter Mentions Network},
	  author    = {R. Sudhesh Solomon and  P. Y. K. L. Srinivas and  Abhay Narayan and  Amitava Das},
	  country	= {},
	  institution	= {},
	  abstract     = {Users in social networks either unicast or broadcast
their messages. At mention is the popular way of unicasting for
Twitter whereas general tweeting could be considered as broadcasting
method. Understanding the information flow and dynamics within
a Social Network and modeling the same is a promising and an
open research area called Information Diffusion. This paper seeks an
answer to a fundamental question - understanding if the at-mention
network or the unicasting pattern in social media is purely random
in nature or is there any user specific selectional preference? To
answer the question we present an empirical analysis to understand
the sociological aspects of Twitter mentions network within a social
network community. To understand the sociological behavior we
analyze the values (Schwartz model: Achievement, Benevolence,
Conformity, Hedonism, Power, Security, Self-Direction, Stimulation,
Traditional and Universalism) of all the users. Empirical results
suggest that values traits are indeed salient cue to understand how
the mention-based communication network functions. For example,
we notice that individuals possessing similar values unicast among
themselves more often than with other value type people. We also
observe that traditional and self-directed people do not maintain very
close relationship in the network with the people of different values
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {12},
	  number    = {8},
	  year      = {2018},
	  pages     = {638 - 643},
	  ee        = {https://publications.waset.org/pdf/10009415},
	  url   	= {https://publications.waset.org/vol/140},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 140, 2018},