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{{Refimprove|date=April 2011}}
'''Social data analysis''' is the data-driven analysis of how people interact in social contexts, often with data obtained from [[Social networking service|social networking services]]. The goal may be to simply understand human behavior or even to propagate a story of interest to the target audience. Techniques may involve understanding how data flows
Social data analysis usually comprises two key steps:
Social data analysis can provide a new slant on [[business intelligence]] where social exploration of data can lead to important insights that the user of analytics did not envisage/explore. The term was introduced by [[Martin M. Wattenberg|Martin Wattenberg]] in 2005<ref>2005: [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.84.6185&rep=rep1&type=pdf Baby Names, Visualization, and Social Data Analysis] Martin Wattenberg. IEEE Symposium on Information Visualization.</ref> and recently also addressed as big social data analysis in relation to [[big data]] computing.
Systems are available to assist users in analyzing social data. They allow users to store [[Data set|data sets]] and create corresponding visual representations. The discussion mechanisms often use frameworks such as a [[blog]]s and [[wiki]]s to drive this social exploration/[[Collaborative intelligence]].
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==Methods of analysis==
In most cases, we want to find out the relationships between social data and another event or we want to get interesting results from social data analyses to predict some events. There are some outstanding articles in this field, including ''Twitter Mood Predicts The Stock Market'',<ref>{{cite journal|last1=Bollen|first1=Johan|last2=Mao|first2=Huinan|last3=Zeng|first3=Xiaojun|title=Twitter mood predicts the stock market|journal=Journal of Computational Science|date=2011|volume=2|issue=1|pages=1–8|arxiv=1010.3003|doi=10.1016/j.jocs.2010.12.007|s2cid=14727513}}</ref> ''Predicting The Present With Google Trends''<ref>{{cite journal|last1=Choi|first1=Hyunyoung|last2=Varian|first2=Hal|title=Predicting the present with google trends|journal=Economic Record|date=2012|volume=88|issue=s1|pages=2–9|url=http://people.ischool.berkeley.edu/~hal/Papers/2011/ptp.pdf|doi=10.1111/j.1475-4932.2012.00809.x|s2cid=155467748}}</ref> etc. In order to accomplish these goals, we need the appropriate methods to do the analyses. Usually, we use [[statistic]] methods, methods of [[machine learning]] or methods of [[data mining]] to do the analyses.
Universities all over the world are opening graduate program in Social Data Analysis.
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==Key concepts==
When talking about social data analytics, there are a number of factors it's important to keep in mind (which we noted earlier):<ref
* '''Sophisticated Data Analysis''': what distinguishes social data analytics from sentiment analysis is the depth of the analysis. Social data analysis takes into consideration a number of factors (context, content, sentiment) to provide additional insight.
* '''Time consideration''': windows of opportunity are significantly limited in the field of social networking. What's relevant one day (or even one hour) may not be the next. Being able to quickly execute and analyze the data is an imperative.
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* [[Collaborative intelligence]]
* [[Social analytics]]
* [[Social data revolution]]
* [[Economic and Social Data Service]]
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{{Reflist}}
[[Category:
[[Category:Collective intelligence]]
[[Category:Social information processing]]
[[Category:Internet terminology]]
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