Jul 162013

With the widespread adoption of social media sites such as Facebook/Linkedin/Twitter and the increasing interest in multimedia sites such as YouTube and Instagram, social media has become one of the larger sources of Big Data. This increased volume of data has created a slew of new IT issues to consider — the most significant one being “What do we do with all this data?” As a result, we’re seeing an increased demand for more storage capacity, enhanced needs for compute power and the introduction of new technologies (such as Hadoop), making the investment to undertake a social media monitoring campaign no small task.

With any substantial investment in new technology comes the question of value. Is there enough value in analyzing social media data to justify the expense and effort to examine this mountain of unstructured data? At some point senior management must wonder if it’s really worth it. Are we learning anything new from this analysis? Is there sufficient value in the insights and knowledge gleaned to justify the investments in this new technology?

An upcoming issue of Cutter IT Journal with Guest Editors Matthew Ganis and Avinash Kohirkar addresses the value of big data analysis and invites practical guidance, insight and actual case studies on whether or not the knowledge and insight derived from this data is worth the resources spent. We also seek to reveal the challenges organizations will encounter implementing this new paradigm into their market research practices.

Topics may include, but are not limited to the following:

* What are the opportunities associated with social media analysis?
* How do you measure the business value (or real value) of your derived insights?
* What metrics do you collect, analyze and then associate with business value?
* How can corporate IT effectively serve its internal clients using social media analytics?
* What are the IT implications of processing social media content (ie, privacy, infrastructure, security)?
* What are the intangible benefits to big data (career growth, technology upgrades, etc)?
* What are the real demonstrable benefits of social media analysis?
* What are the pros and cons of “actively” engaging with consumers on social media channels?
* Is there a best of breed “methodology” for approaching a social media analytics project?
* What are the implications to the data center as a result of processing/storing/managing high volumes of data?
* Are there any use cases describing the combination of predictive analytics with social media data?
* Are there real benefits to “listening” to what people are saying on Twitter?
* Do you analyze social media influencers? If so, how do you determine who is influential? What are the attributes of social media influencers and how do you measure their credibility?
* Is there a minimum set of skills analysts should have? Is there a certification path or a standard?
* How global is the social media phenomenon? (For example, is the value of social media analysis in China the same as in the United States? Are there cultural differences in the use of social media that need to be taken into consideration)?
* Is there any “value” to storing vast amounts of this data in our enterprise databases?
* How do you turn the data from social media into actionable insight to deliver business value?
* How can or should you interpret social media findings given that the population of participants is not likely to be representative of the entire target population?
* If we are to rely on social media analytics, can hacking or deliberate infusion of misinformation (or volume) be detected quickly?
* Is social media listening worthwhile in a B2B enterprise, or is this for B2C companies only? Is building social media listening queries an art or a science?


Please respond to the Guest Editor Matt Ganis, ganis[at]us[dot]ibm[dot]com with a copy to Christine Generali, cgenerali[at]cutter[dot]com no later than 26 July 2013 and include an extended abstract and a short article outline showing major discussion points.

Accepted articles are due by 30 August 2013.

Editorial Guidelines


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