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.

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Social data analysis usually comprises two mainkey constiuent 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''' 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">

{{cite book

| author = Erik Cambria

|author2=Dheeraj Rajagopal |author3=Daniel Olsher |author4=Dipankar Das

| title = Big social data analysis

| booktitle = Big Data Computing

| chapter = 13

| year = 2013

| publisher = Taylor & Francis

| url = http://tmrfindia.org/bigdata.html

}}

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

'''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 <refin namerelation =to "Cambria13">[[big data]] computing.

Social data analysis comprises two main constiuent parts: 1) 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 analytics, 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 = "IBM Emerging Technology"> [http://www-01.ibm.com/software/ebusiness/jstart/socialdata/ IBM Emerging Technology - jStart - On the Horizon - Social data analytics] </ref>

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]].

==Obtaining social data==

==Basic Definition==

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]].

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]].

Some [[API|APIs]] only allow access to data in small quantities, hence indexing the data in bulk 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].

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).

==Methods of Analysesanalysis==

==How To Get Social Data==

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> and 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.

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. Social data can also be fetched by adding [[social login]] by using various plugins or add-ons depending on the CMS [[webmaster]] is using. It can also be helpful for the marketers who do not have coding skills to add APIs manually. <ref>{{cite web|last1=Sen|first1=Subhro|title=Why Savvy Marketers Are Hooked on Social Data|url=http://blog.loginradius.com/2014/07/marketers-social-data/|website=Loginradius.com|publisher=LoginRadius Inc.}}</ref>

==Methods of Analyses==

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}}</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}}</ref> and 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=":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.

* '''Influence Analysis''': understanding the potential impact of specific individuals can be key in understanding how messages might be resonating. It's not just about quantity, it's also very much about quality.

* '''Network Analysis''': social data is also interesting in that it migrates, grows (or dies) based on how the data is propagated throughout the network. It's how viral activity starts--andstarts—and spreads.

== See also ==

* [[Data Analysis]]

* [[Big Data]]

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* [[Collaborative intelligence]]

* [[Social analytics]]

* [[IBM jStart]]

* [[Social data revolution]]

* [[Economic and Social Data Service]]

==External links==

* [http://www.socialdata.com.br Social Data - Ferramenta para Redes Sociais]

* [http://researchweb.watson.ibm.com/visual/social_data_analysis_workshop/ Social Data Analysis Workshop at CHI 2008]

* [http://csdl2.computer.org/persagen/DLAbsToc.jsp?resourcePath=/dl/trans/tg/&toc=comp/trans/tg/2006/04/v4toc.xml&DOI=10.1109/TVCG.2006.65 Designing for Social Data Analysis]

* [http://www.istrategylabs.com/2011/09/announcing-grandstand-a-social-data-product-for-rewarding-crowds/ Social Data Analysis Application: Grandstand]

* [http://sentic.net/mabsda Multidisciplinary Approaches to Big Social Data Analysis (WWW13 workshop)]

* [http://MiningTheSocialWeb.com Mining the Social Web (website)]

* [http://www.amazon.com/gp/product/1449367615 Mining the Social Web, 2nd Edition (O'Reilly Media, 2013)]

* [http://2011-textbook-deals.info/wp-content/uploads/pdfs/Statistics%20for%20social%20data%20analysis%20by%20George%20W%20Bohrnstedt%20-%20Indoctrination%20By%20Statistical%20Methodology.pdf Statistics for social data analysis (Bohrnstedt, George W, and David Knoke, 1994)]

* [http://www.goodreads.com/book/show/3951998-qualitative-data-analysis Qualitative data analysis: A user friendly guide for social scientists (Dey, Ian, 2003)]

* [http://www.amazon.com/Longitudinal-Panel-Data-Analysis-Applications/dp/0521535387 Longitudinal and panel data: analysis and applications in the social sciences (Frees, Edward W, 2004)]

* [http://www.amazon.com/Analyzing-Social-Science-Data-Problems/dp/0761959386 Analyzing social science data: 50 key problems in data analysis (De Vaus, David 2002)]

* [http://www.amazon.com/Methods-Network-Analysis-Structural-Sciences/dp/0521600979 Models and methods in social network analysis (Carrington, Peter J., John Scott, and Stanley Wasserman, eds 2005)]

* [http://www.computer.org/csdl/proceedings/afips/1965/5066/00/50660533.pdf Data analysis in the social sciences: What about the details? (Ball, Geoffrey H, 1965)]

* [http://www.amazon.com/Analysis-Sciences-Undergraduate-Research-Statistics/dp/0761987363 Data analysis in the social sciences: What about the details? (Aneshensel, Carol S, 2012)]

==References==

{{Reflist}}

[[Category:VisualizationData (graphic)and information visualization]]

[[Category:Collective intelligence]]

[[Category:Social information processing]]

[[Category:Internet terminology]]