The document discusses the integration of social media data into social science research, highlighting the emergence of big data, data science, and an expanding marketplace for data analysis. It details various methodologies for analyzing social media behavior, including monitoring, tracking, networking, and mapping, along with specific metrics used for evaluation. Additionally, the document emphasizes the importance of effective communication of research findings through academic and visual tools.

1. SOCIAL MEDIA DATA FOR
SOCIAL SCIENCE RESEARCH
Davide Bennato
Università di Catania
dbennato@unict.it
@tecnoetica

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3. SOCIAL SCIENCE & SOCIAL MEDIA
CONTEXT

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http://www.flickr.com/photos/intelfreepress/6780720740

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• Big Data
 New sources of data: mobile log, social media activity, sensors
 New industries: SAAS, social platforms, mobile, BI
 New research landscapes: huge dataset of human behaviour
http://www.mushroomnetworks.com/infographics/landscape-of-big-data

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https://community.informatica.com/solutions/making_sense_of_big_data

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http://www.dr4ward.com/dr4ward/2013/01/what-is-big-data-and-what-are-some-tools-for-analytics-infographic.html

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http://www.fico.com/landing/infographic/The-Analytics-Big-Bang-Infographic.pdf

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http://www.forbes.com/sites/davefeinleib/2012/06/19/the-big-data-landscape/

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http://www.capgemini.com/technology-blog/2012/09/big-data-vendors-technologies/

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http://www.zdnet.com/blog/hinchcliffe/the-enterprise-opportunity-of-big-data-closing-the-clue-gap/1648

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• Data Science
 When worlds collide: statistics/math, computer skills,
 Data scientist from the social science point of view is a
computational social scientist
http://smartdatacollective.com/davidmsmith/124376/statistics-vs-data-science-vs-bihttp://www.drewconway.com/zia/?p=2378

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http://nirvacana.com/thoughts/becoming-a-data-scientist/

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• Data Market
 A growing marketplace: digital marketing, Big Data industry
 Data companies: monitoring platform (Radian6)
 Data services: Freebase, Datahub
http://www.quintly.com/blog/2013/03/infographic-the-rise-of-social-media-analytics/

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http://www.forbes.com/sites/gilpress/2013/03/18/top-10-most-funded-big-data-startups/

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http://www.crunchbase.sisense.com/#big-data-investments/c7i9

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http://socialmediaswitzerland.org/2012/07/11/goldbach-interactives-social-media-monitoring-tool-report-2012/

18. SOCIAL SCIENCE & SOCIAL MEDIA
RESEARCH TRADITIONS

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http://en.wikipedia.org/wiki/Computational_sociology

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• Digital methods (https://www.digitalmethods.net/)
 A set of methodologies used for analysing social behaviour in
the web
 Scientific tradition: social research, media studies
http://adequatebird.com/2010/05/03/the-political-blogosphere-and-the-2004-u-s-election-divided-they-blog/

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• Social media mining
 A group of techniques to extract relevant information from a
social media dataset
 Scientific tradition: datamining, computer science
https://www.facebook.com/notes/facebook-engineering/visualizing-friendships/469716398919

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• Social media analytics
 A group of tools and services for the evalution of the social
media ROI (return on investments)
 Scientific tradition: digital marketing, webmetrics
http://inmaps.linkedinlabs.com/

23. RESEARCH STRATEGIES
IN SOCIAL MEDIA

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• Monitoring
 Searching for particular words/query/topics
 Unit of analysis: Words
http://slackprop.wordpress.com/2013/06/03/on-geek-versus-nerd/

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• Tracking
 Analyzing a set of users choosen in a specific way
 Unit of analysis: social media account

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• Networking
 Analyzing relationship between a set of social media users
 Unit of analysis: relationship
http://blog.socialflow.com/post/5246404319/breaking-bin-laden-visualizing-the-power-of-a-single

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• Mapping
 Analyzing geo-spatial properties of a set of social media data
 Unit of analysis: space
http://www.flickr.com/photos/twitteroffice/sets/72157633647745984/

29. RESEARCH DESIGN

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(Welser, Smith, Fisher, Gleave, 2008)

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http://www.debajyoti.net/socialmedia/social-analytics-lifecycle-and-social-media-strategy-a-graphical-framework.html

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• Decide which metrics collect
 Which is the problem we want to study?
 Which are indicators we need to study the problem?
http://www.seratoo.com/MarketingWeb2.0/infographic-a-guide-to-analytics-based-online-marketing/

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• Collect data
 Create a database with the data we want to study
 Script approach: Python (e.g.)
 Softwares: ScraperWiki, NodeXL
http://www.seratoo.com/MarketingWeb2.0/infographic-a-guide-to-analytics-based-online-marketing/

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• Analizing data
 Statistically: using simple measures to describe data
 Visually: using a graphical way to understand data
http://www.seratoo.com/MarketingWeb2.0/infographic-a-guide-to-analytics-based-online-marketing/

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• Interpreting data
 Relations between metrics/indicators and research questions
 Data storytelling approach
http://www.seratoo.com/MarketingWeb2.0/infographic-a-guide-to-analytics-based-online-marketing/

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• Communicating results
 Academic tools: paper, report
 Communication tools: infographics, visualizations
http://www.seratoo.com/MarketingWeb2.0/infographic-a-guide-to-analytics-based-online-marketing/

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http://visual.ly/what-infographic-2

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http://visual.ly/
http://infogr.am/

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http://piktochart.com/
http://www.easel.ly/

40. TWITTER

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• Why Twitter?
 A growing platform in information diffusion (influencer, events)
 A complete set of API (Rest API, search API, streaming API)
 Simple metrics for complex analysis

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• Search API
 Sample of tweet
 Is unclear which is the method
of sampling
• Streaming API
 An extendend sample of tweet
(Morstatter, Pfeffer, Liu,
Carley, 2013)
• Rest API
 Following, follower
 Trending topic (per
nation/day/week)
 Last 20 status update
 Last 100 recent tweets
 Last 100 users retwitting
another one
 …

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http://readwrite.com/2010/04/19/this_is_what_a_tweet_looks_like

44. TWITTER
METRICS

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http://www.dosisdiarias.com/2012/08/100.html

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• Metrics: tweet
 What: number of messages (amount, time-based)
 Used for: popularity, participation, audience
https://twitter.com/Tecnoetica/status/357481799431110657

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• Metrics: retweet
 What: reposting a tweet (amount, time-based, accounts)
 Used for: popularity, diffusion, spreading, virality
https://twitter.com/Tecnoetica/status/357481799431110657

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• Metrics: mention/reply
 What: a tweet direct to @somebody/answer to a tweet
 Used for: relationship studies, SNA on Twitter
https://twitter.com/Tecnoetica/status/357481799431110657

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• Metrics: words
 What: Which and how many words are used in the tweets
 Used for: topic analysis, sentiment analysis
https://twitter.com/Tecnoetica/status/357481799431110657

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• Metrics: hashtag
 What: a #keyword used for describe tweet’s content
 Used for: topic analysis, event analysis
https://twitter.com/Tecnoetica/status/357481799431110657

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• Metrics: accounts
 What: How many @people tweet during an event or about a
#topic
 Used for: popularity, audience analysis,
https://twitter.com/Tecnoetica/status/357481799431110657

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• Metrics: follower
 What: Accounts following by a user
 Used for: interest analysis, community detection

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• Metrics: following
 What: account that a user are following
 Used for: interest analysis, community detection

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• Other metrics:
 Favorite: tweets preferred by a user (semamntic: like, read-later)
 Lists: a number of account with similarrities according a user

55. TWITTER
TOOLS

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• Twitter counter http://twittercounter.com/
 Research strategy: tracking
 Metrics: tweets (time based), followers (time based), following,

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• Tweet stats http://www.tweetstats.com/
 Research strategy: tracking
 Metrics: tweets (time based), reply, source, retweet, word,
hashtag,

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• Mentionmapp http://mentionmapp.com/
 Research strategy: networking
 Metrics: followers, hashtags

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• Spot http://neoformix.com/spot/
 Research strategy: tracking, monitoring
 Metrics: similar tweets, tweet by time, most active accounts,
words, source (sending tool), tweet containing common words

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• Tweet Archivist http://www.tweetarchivist.com/
 Research strategy: monitoring
 Metrics: top user, word cloud, top URL, source, Tweet by time,
mentions, hashtags, collecting dataset ($)

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• Twittonomy http://www.twitonomy.com
 Research strategy: tracking, monitoring, mapping (mentions)
 Metrics: tweets, following, followers, lists, favorites, timeline,
hashtag, collecting dataset ($)

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• Tweet Topic Explorer http://tweettopicexplorer.neoformix.com
 Research approach: tracking
 Metrics: words (last 800 tweets)

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• Tweepsmap http://tweepsmap.com/
 Research strategy: account mapping
 Metrics: mapping followers

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• Simply Measured Following Report
http://simplymeasured.com/free-social-media-tools#report-20
 Research strategy: follower analysis
 Metrics: time zone, rank for followers, last tweet date rank,
https://app.simplymeasured.com/viewer/8dlkwkpcz7h82escv8ij6xc22ri3ap/1196194?id=563284#

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• Wordtree http://www.jasondavies.com/wordtree/
 Research strategy: tracking
 Metrics: words (in contexts)

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• Wildfire Monitor https://monitor.wildfireapp.com/
 Research strategy: tracking
 Metrics: followers, followings, tweets

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• Collecting tweets:
 Tweet archivist desktop:
http://www.tweetarchivist.com/archivist-desktop/
 NodeXL: http://nodexl.codeplex.com/

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• Analyzing relationship (SNA approach)
 NodeXL: http://nodexl.codeplex.com/
 Gephi: https://gephi.org/

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• Networking case study
 The spread of the news of the resignation of Benedict XVI
 Data source: Keleyo (http://keleyo.it/)

71. LIPARI21/07/2013
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• Bigliography
 Giglietto F., Rossi L., Bennato D., 2012, The Open Laboratory:
Limits and Possibilities of Using Facebook, Twitter, and YouTube
as a Research Data Source, “Journal of Technology in Human
Services”, vol.30, n.3-4, pp.145-159.
 Hansen D.L., Shneiderman B., Smith M. a., 2011, Analyzing
social media networks with NodeXL, Elsevier, Amsterdam.
 Morstatter F., Pfeffer J., Liu H., Carley K. M. 2013, Is the Sample
Good Enough? Comparing Data from Twitter’s Streaming API
with Twitter’s Firehose, arXiv, 21 june 2013,
http://arxiv.org/abs/1306.5204
 Welser H. T. , Smith M., Fisher D., Gleave E., 2008, Distilling
digital traces: Computational social science approaches to
Studying the Internet, in Fielding N., Lee M. L., Blank G., The
SAGE Handbook of online research methods, SAGE, London,
pp.116-140.

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• Davide Bennato teaches Sociology of culture
and communication and Sociology of digital
media at the Department of Humanistic Sciences
at the University of Catania.
• He was professor for different italian universities:
Roma “La Sapienza”, LUISS, Università di Siena,
Università del Molise.
• He is one of the founding members of STS-Italia
(Science and Technology Studies Italian
Association) and was vice-president (2005-08).
He is also founding member of Startup CT,
association for the promotion enterpreneurial
startup business culture. He is member of the
board of Bench s.r.l., a University of Catania spin
off in social and marketing researches.
• His research topics are: technological cultures,
digital content consumptions, social media
interpersonal relationship.
• Books: Le metafore del computer. La
costruzione sociale dell’informatica (Meltemi,
2002) e Sociologia dei media digitali (Laterza,
2011).
• Books chapters: (2010) voce La circolazione
delle tecnologie, in XXI Secolo, Istituto
dell’Enciclopedia Italiana Giovanni Treccani,
(2011) Strategie di relazione sociale nelle
piattaforme di social network, (2012) Etica dei
social network. Valori e comportamenti sociali in
Facebook, (2013) Morte di un’icona pop. Le
reazioni online alla morte di Michael Jackson.

73. LIPARI21/07/2013
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• Davide Bennato
 Sociologia dei media digitali, Laterza, Roma-Bari, 2011
• Millions of people consult and interact with each other through
the use of internet. Each in its own way, participate in the
networking of news, but also to the transformation of these
tools of communication and socialization. Blogs, wikis, social
networks are - above all - tools of social relationship. The
participative web then obliges a profound rethinking of the
classical concepts of the sociology of communication.
• Davide Bennato offers a detailed analysis of the different tools
and platforms well known to the public, from Facebook to
Youtube, and examines the ethical and social consequences
of the use of new technologies.
• The book on internet
 website
 http://www.sociologiadeimediadigitali.it
 Facebook fanpage
 http://www.facebook.com/sociologiadei
mediadigitali
 Twitter
 http://twitter.com/mediadigitali

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Socialmedia
http://twitter.com/tecnoetica
http://www.facebook.com/davide.bennato
http://www.linkedin.com/in/davidebennato
http://www.youtube.com/tecnoetica
http://pinterest.com/davidebennato/
Skype
davide.bennato
Blog
www.tecnoetica.it
www.processiculturali.it
www.sociologiadeimediadigitali.it