Changes

 *Fundamentally, one ought to think of Twitter as an interest group, not a bona fide social network. Analogously, Consider this: Twitter represents the degree of interest in, for instance, '''#ycombinator''', not the stable business and personal connections made to and fro '''@ycombinator'''. It also houses everyone from the very important @barackobama to the fictional and frivolous @homersimpson. At the outset, Twitter represent trends than material fact. The following-follower relationship is mono-directional and voyeuristic, representing what people care and think about, instead of who they really are and what they really do. Twitter activity happens at the speed of thought (140 chars) and represents our rapidly-changing minds and perceptions.

 *Digging a little deeper beyond the this superficial exchange, we come to a point where we need to think qualitatively about tweets. What people care about reflects some material facts about their material selves. , Tweets containing hashtags such as #kpceoworkshop, for instance, tells us which people are attending the event physically and which accelerator signed people are passing commentary on it. When a startup has an IPO/Acquisition, it will attract a tremendous volume of mentions. When the presidential candidates talk about their technology policies, the entrepreneurship twitterverse responds. <blockquote>This is the next level of Twitter mining, often associated with To mine TwitterNatural Language Processing techniques: '''Tweet Analytics'''. From tweets, we can learn about events that are unfolding in the entrepreneurship world, thereforeas well as new organizations that appear in the conversation. When measured over time, is to be interested we can get a handle on the up-and-coming stars in the field, and emerging trendsthat are of note.  *The three most prominentOn a even more physical level, popular tweets contain geo-information such as @user's home location and important the tweet-from location. Through this, we stand to learn about the people's interests stratified by location. When combined with the former two forms of Twitter twitter mining , it can enhance what we know about physically-bound social dynamics and physically-bound shifts in interest and opinions.<blockquote>'''Geo Visualization''' is the process of mapping tweets to a real map of the Earth. Applying '''tweet analytics''' and '''network visualization''' to it, we stand to have a better picture of the ongoings in terms of peoeple, organizations and events in particular places, for instance Palo Alto, CA or Austin, TX. When measured over time, we can observe the crests and troughs of activity in these places. This would be classified loosely into 3 categories:extremely promising especially for the '''HUBS''' research project. #Twitter analytics