Integrating Web-based Intelligence Retrieval and Decision-making from the Twitter Trends Knowledge Base

Abstract

The microblogging site Twitter has a lot of room to grow into a centralized database of information useful for gathering perspectives,
facts, ideas, and feelings. Activated knowledge-base decision-making with communal intelligence retrieval is the topic
of this research. Because we are analyzing tweets from microblogs rather than the more typical “blogosphere,” our technique
is distinct from that of the current research. To further differentiate our process, we combine visualization tools with data
mining methods based on artificial intelligence to categorize communications related to the trend subject. In addition to trying
to correlate a Twitter trend with real-world events, our technique examines the demographics of the people who post such
tweets. Through the use of visualization techniques, we are able to deduce a pattern from Twitter trends and see its ‘ticking’ and
evolution. We get a fresh view on the people who start trends from our research, which helps us identify the ‘trend setters’ and
their underlying traits.