Evolving social data mining and affective analysis methodologies, framework and applications

Abstract

Social networks drive todays opinions and content diffusion. Large scale, distributed and unpredictable social data streams are produced and such evolving data production offers the ground for the data mining and analysis tasks. Such social data streams embed human reactions and inter-relationships and affective and emotional analysis has become rather important in todays applications. This work highlights the major data structures and methodologies used in evolving social data mining and proceeds to the relevant affective analysis techniques. A particular framework is outlined along with indicative applications which employ evolving social data analysis with emphasis on the seminal criteria of topic, location and time. Such mining and analysis overview is beneficial for various scientific and enterpreneural audiences and communities in the social networking area.