PROJECT TITLE :

Facilitating Time Critical Information Seeking in Social Media - 2017

ABSTRACT:

Social media plays a significant role in helping individuals stricken by natural calamities. These individuals use social media to request information and help in things where time is a essential commodity. However, generic social media platforms like Twitter and Facebook aren't conducive for obtaining answers promptly. Algorithms to confirm prompt responders for queries in social media should perceive and model the factors affecting their response time. In this paper, we tend to draw from sociological studies on info seeking and organizational behavior to identify users who can provide timely and relevant responses to queries posted on social media. We have a tendency to 1st draw from these theories to model the longer term availability and past response behavior of the candidate responders and integrate these criteria with user relevance. We tend to propose a learning algorithm from these criteria to derive optimal rankings of responders for a given question. We present queries posted on Twitter as a type of information seeking activity in social media and use them to guage our framework. Our experiments demonstrate that the proposed framework is helpful in identifying timely and relevant responders for queries in social media.