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Twitter and Facebook Analysis: It’s Not Just for Marketing Anymore

INTRODUCTION Recently, companies have discovered that social media analytics is crucial, especially for customer feedback and building goodwill. The analytics allow marketers to identify sentiment and detect trends in order to better accommodate the customer. There have been significant examples where companies, such as the airline industry, have used such analytical tools to reach customers based on feedback received. Marketers aren’t the only ones thinking about social media analytics. Despite the difficulties in analyzing social media, law enforcement has realized there is a wealth of free public information floating around on social media sites with the potential to aid in investigation and crime prevention. While companies are mainly interested in what social media has to say about their brand and their products, law enforcement agencies have two challenges in collecting and analyzing social media data that are unique to their goals. First, they are not always sure what subjects and key words they are looking for. Much of the intelligence in the data must be developed up front in order to determine what to search for in say, the Twitter stream. Second, they are restricted to “publicly” available social media data. They must be able to gather the data anonymously and without authentication tokens that require user approval. In this paper, we will outline the concept and execution of two social media analytics applications that use SAS to address law enforcement issues. The applications incorporate social media in very different ways. The first is as an investigative tool to find social media related to specific people. Using an adaptation of our Social Network Analysis (SNA), we present Facebook and Twitter searches of multiple suspects in an easily digestable form for the analyst. The second application focuses on monitoring social media across a much broader spectrum, looking for the proverbial “needle in a haystack”. In this example, we show how to collect and analyze historical Twitter data to try to understand precursors to dangerous activity at events, such as riots at concerts or flash mobs.

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