• K. Victor Rajan

Social media analytics is the process of gathering and analyzing audience data shared on social networks to improve strategic decisions. The World Wide Web such as social networks, forums, blogs, and review sites emit large volume of data in the form of opinions, emotions, and sentiment on various public events, government policies, political protests, etc. Decision makers can make use of social media to understand how people react to policies, events, and consumer products. But social media analytics is a challenging task due to the complexity of natural language processing of social media language. The severity of the crisis and the length of time that it languishes unmitigated, or worse unseen, may bring critical consequences to society that can linger for years. Having a social media analytics tool is great. Research has already been done to extract opinion, sentiment, etc., from social media using computational techniques. Some researchers focus on extracting sentiment or emotion from text messages. Let’s say, analytics indicate positive sentiment over a government policy and upward growth of a hashtag related to an electronic gadget. How to decide whether they are related? Analysis of the symbiotic relationship between events is necessary to derive meaningful conclusions. Using disparate data analysis tools or sources is an unnecessary headache that we don’t have to deal with in extracting actionable intelligence from data. Our research tries to solve the problems that analysts face when stitching their social media analysis together from disconnected sources by offering a one-and-done solution. In other words, it’s a next-level social media analytics tool that synthesizes your data to establish a cohesive and easily understandable window into the online narrative. Social Event Semantic Network uses Artificial Intelligence to deep dive into any social media topic to provide complete coverage of events including sentiment, impact, inter-relationship etc., to provide a holistic view to strategic decision makers. Main advantage of our approach allows you to see the interconnectivity between adjacent social sub-conversations. This visualization allows framework users to quickly understand the event through various angles from which target audiences are talking about a topic or issue.

Social Media Analytics, Opinion Mining, Semantic Networks

"Social Event Semantic Network: Framework for Social Media Coverage using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.e176-e182, May-2023, Available :http://www.jetir.org/papers/JETIR2305426.pdf

"Social Event Semantic Network: Framework for Social Media Coverage using Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppe176-e182, May-2023, Available at : http://www.jetir.org/papers/JETIR2305426.pdf