Social data analysis: Difference between revisions

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'''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 within a network, identifying influential nodes (people, entities etc.), or discovering trending topics.

Social data analysis usually comprises two key steps: 1) gathering data generated from social networking sites (or through social applications), and 2) analysis of that data, in many cases requiring real-time (or near real-time) data analysis, measurements which understand and appropriately weigh factors such as influence, reach, and relevancy, an understanding of the context of the data being analyzed, and the inclusion of time horizon considerations. In short, social data analytics involves the analysis of social media in order to understand and surface insights which is embedded within the data.<ref name=":0">{{Cite web |date=2012-01-19 "|title=IBM Emerging Technology">[Technologies - jStart - On The Horizon - Social Data Analytics |url=http://www-01.ibm.com/software/ebusiness/jstart/socialdata/ IBM Emerging Technology|archive-url=https://web.archive.org/web/20130425062954/http://www-01.ibm.com/software/ebusiness/jstart/socialdata/ |archive-date=2013-04-25 jStart |access-date=2025-08-26 On the Horizon |website=www-01.ibm.com Social data analytics]|language=en-US}}</ref>

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.

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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 name = "IBM Emerging Technology:0" />

* '''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]]

* [[IBM jStart]]

* [[Social data revolution]]

* [[Economic and Social Data Service]]

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{{Reflist}}

[[Category:Data and information visualization]]

[[Category:Collective intelligence]]

[[Category:Social information processing]]

[[Category:Internet terminology]]