Social data analysis: Difference between revisions

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

'''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 in relation to [[big data]] computing.

Social data analysis usually comprises two mainkey constituent partssteps: 1)gathering data generated from social networking sites (or through social applications), and 2) sophisticated analysis of that data, in many cases requiring real-time (or near real-time) data analyticsanalysis, 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''' iscan provide a stylenew ofslant analysison in[[business whichintelligence]] peoplewhere worksocial inexploration aof social,data collaborativecan contextlead to makeimportant senseinsights that the user of dataanalytics 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.

==Basic definition==

OnSystems aare Socialavailable Datato Analysisassist systemusers orin network,analyzing users storesocial data sets and create visual representations. TheThey datasetsallow and visualisations/graphs are accessibleusers to otherstore users[[Data ofset|data thesets]] network or website. Users canand create newcorresponding andvisual interesting visualisations/graphs as well as associated commentary from the same data setsrepresentations. The discussion mechanisms often use frameworks such as a [[blog]]s and [[wiki]]s to drive this social exploration/[[Collaborative intelligence]].

==How to getObtaining social data==

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).

Social networking services are increasingly popular with the development of [[Web 2.0]]. Many of these services provide [[API|APIs]] that allow easy access to their data by responding to user queries with the requested data in the form of [[XML]] or [[JSON]] formatted strings. In order to protect privacy of their users, services such as [[Facebook]] require that the person requesting data has the necessary data access permissions. Services may also charge users for access to their data. Sources of social data include [[Twitter]], [[Facebook]], news websites, [[Wikipedia]] and [[We Feel Fine]].

==How to get social data==

IndexingSome the[[API|APIs]] only allow access to data in bulksmall canquantities, behence harderindexing thanthe accessingdata simplerin APIsbulk can become a challenge. [[Six_Apart]] was the first social media company to provide a (free) firehose of content for all the posts in their network (provided over XMPP). Twitter later came along and provided a firehose as did companies like [http://spinn3r.com Spinn3r], [http://datasift.com Datasift], and [http://gnip.com GNIP].

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]] 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. Social data can also be fetched by adding [[social login]].

Indexing the data in bulk can be harder than accessing simpler APIs. [[Six_Apart]] was the first social media company to provide a (free) firehose of content for all the posts in their network (provided over XMPP). Twitter later came along and provided a firehose as did companies like [http://spinn3r.com Spinn3r], [http://datasift.com Datasift], and [http://gnip.com GNIP].

==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:VisualizationData (graphic)and information visualization]]

[[Category:Collective intelligence]]

[[Category:Social information processing]]

[[Category:Internet terminology]]