Presentation Title
Degree Name
Master of Computer Science and Systems (MCSS)
Department
Institute of Technology
Location
Tioga Library Building
Start Date
26-5-2014 4:50 PM
End Date
26-5-2014 4:55 PM
Abstract
Emotions are definitely contagious :-). While obvious in most face-to-face interactions, is that also true in massive online social networks such as Facebook and Twitter? If emotions do propagate online, then a key question is whether different emotions, such as sadness or joy, spread equally in the same pattern or at the same rate. In addition, are there common characteristics between spread of emotion online vs in real life as quantified by susceptibility of our friends to be influenced by our own emotions? Assuming we can infer personalities based on user generated content, what role does the personality of each social network actor play in this online emotion propagation?
In our research we are building a predictive model that can infer the emotion propagation pathways within a social network. We intend to demonstrate the utility of our model to analyze users who are most likely to evoke a particular emotion, say anger or sadness, given that we know the content they have shared and who their friends are in the social network. Needless to state, developing such a predictive model is challenging and fun, and at the same time immensely useful to understand emotional trends across society; which in-turn can help shape social policy, provide business opportunities, and identify members of the community who may be psychologically at risk.
COinS
Emotion Propagation in Online Communities
Tioga Library Building
Emotions are definitely contagious :-). While obvious in most face-to-face interactions, is that also true in massive online social networks such as Facebook and Twitter? If emotions do propagate online, then a key question is whether different emotions, such as sadness or joy, spread equally in the same pattern or at the same rate. In addition, are there common characteristics between spread of emotion online vs in real life as quantified by susceptibility of our friends to be influenced by our own emotions? Assuming we can infer personalities based on user generated content, what role does the personality of each social network actor play in this online emotion propagation?
In our research we are building a predictive model that can infer the emotion propagation pathways within a social network. We intend to demonstrate the utility of our model to analyze users who are most likely to evoke a particular emotion, say anger or sadness, given that we know the content they have shared and who their friends are in the social network. Needless to state, developing such a predictive model is challenging and fun, and at the same time immensely useful to understand emotional trends across society; which in-turn can help shape social policy, provide business opportunities, and identify members of the community who may be psychologically at risk.