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Analytics & Predictive Models for Social Media

Part 1: Information flow in social media (slides) Collecting social media data Extracting and tracking the flow of relevant information Correcting for the effects of missing and incomplete data Predicting and modeling the flow of information Identifying networks of information flow Part 2: Rich user interactions (slides) Predicting and recommending links in network Modeling tie strenght Modeling trust and distrust, frieds and foes How users evaluate one another and the social media content

Abstract Tools for social networking and social awareness are developing rapidly and evolving continuously. They are gaining popularity in a growing number of professional as well as personal activities, including scholarly research. There are social awareness tools for science researchers that facilitate collaboration, help manage references, and offer options for presenting findings in new ways. This paper discusses those tools. Evaluating and understanding their functionalities requires effort, and scientists can be reluctant to invest the necessary time to learn to use and populate them on their own. This suggests that an important role for librarians is to evaluate the many social awareness tools available, to recommend the ones that are best suited to each researcher's needs, and to help researchers use those tools effectively.

2014 may mark the beginning of the end of abysmal customer service at major airlines, credit card companies, banks, and other repeat offenders,

Twitter, for instance, just unveiled a feature enabling paid Tweets to be targeted by zip code.

This kind of "geo-fencing," which Facebook has had since 2011, enables businesses to court nearby customers who might actually want to get ads offering special deals, in-store specials, etc.

Social Media Content Ideas: A Perpetual Idea System