Social data analysis: Difference between revisions

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<big>* Basic Definition</big><br />

'''Social data analysis''' is a style of analysis in which people work in a social, collaborative context to make sense of data. The term was introduced by [[Martin M. Wattenberg|Martin Wattenberg]] in 2005 <ref>2005: Baby Names, Visualization, and Social Data Analysis Martin Wattenberg. IEEE Symposium on Information Visualization.</ref> and recently also addressed as big social data analysis <ref name = "Cambria13">

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</ref> in relation to [[big data]] computing.

On a Social Data Analysis system or network, users store data sets and create visual representations. The datasets and visualisations/graphs are accessible to other users of the network or website. Users can create new and interesting visualisations/graphs as well as associated commentary from the same data sets. The discussion mechanisms often use frameworks such as a [[blog]]s and [[wiki]]s to drive this social exploration/[[Collaborative intelligence]].

This is a new slant on [[business intelligence]] where social exploration of data can lead to serious analysis and important insight that the initiating user did not envisage/explore (for whatever reason).

<big>* How To Get Social Data</big><br />

With the development of [[Web 2.0]], social networks are more and more popular. More and more scholars are working on social data analyses, hoping to find interesting results from the analyses. Usually, we can retrieve the social data from a variety of social networks, such as [[Twitter]], [[Facebook]], [[We Feel Fine]], [[Wikipedia]] and etc. Since most of the social networks provide us with the [[API]], it's not difficult for us to retrieve the data. Using [[API]] to get data is like sending a request to the website and then the website returns the requested data in form of [[XML]] or in form of [[JSON]]. Since sometimes the data we request is more private, we may need to pay for the [[API]] in order to get the data we want.

<big>* Methods of Analyses</big><br />

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=1-81–8}}</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=2-92–9}}</ref> and etc. In order to accomplish these goals, we need the appropriate methods to do the analyses. Usually, we use [[Statistic|statistic]] methods, methods of [Machine learning|[machine learning]] or methods of [[Data mining|data mining]] to do the analyses.

Universities all over the world are opening graduate program in Social Data Analysis.