The Open laboratory

PRIN 2009 | Social Network Studies Italia

Limiti e possibilità per l’uso di FaceBook, Twitter e YouTube come sorgente dati

Davide Bennato, Università di CataniaFabio Giglietto, Università di Urbino Carlo BoLuca Rossi, IT University of Copenhagen

methodology

We can define it as a problem solving applied to research questions

One methodology, many methods (or tecniques)

Sociological research in social media: the qualitative/quantitative debate is very difficult to apply

Reasons1. Social media are software objects/texts2. Difficulties in applying the concept of representativeness3. Digital texts are performative activities4. Digital texts are culturally embedded

methodologyRicolfi 1997

methodology

Three great models of social research in participative web

1. EthnographyInterpretative approachText as unit of analysis

2. StatisticalMathematical approachQuantification/metrics as unit of analysis

3. ComputationalComputer science approachFormal relationship and unit of analysis

YoutubeVideosharing platform: different use, different metrics

Audience interaction1. visualizations (videos)2. visualizations (channells)

Social interaction1. comments2. I like/I don't like3. friending/subscriptions

Platform interaction1. metadata (tag, video title, ID video, contributor, date added, description)

YoutubeEthnographic research

StrategiesVideos as significative objectUse in small communities (e.g. vloggers)

Research characteristicsSmall size of videos analizedGreat use of different qualitative tecniques (e.g interviews, audio transcriptions)Multi-methods/triangulation approaches preferred

Youtube

Harley, Fitzpatrick 2009

Youtube

YoutubeStatistics research

StrategiesVideo as traces of a social bevahiourVideo as way to access a community (e.g political candidates)

Research characteristicsSampling tecniques: the construction of the universeContent analysis: human or automatic (e.g. Leximancer)Coding tecniques (Grounded Theory)

Youtube

Ricke 2010

Youtube

Klotz 2010

Youtube

Bal 2010

Youtube

Bennato 2012

Youtube

YoutubeComputational research

StrategiesAny software object express something (about platform or about users)Analysis have to consider also platform structural characteristics

Research characteristicsBig/enormous data collectionWeb services approach (e.g. Tubekit, Tubemogul)Alghoritmic approach (Google API manipulations)Modelling (e.g. power law, graph structure)

Youtube

Shra, 2009

Youtube

Youtube

Wallsten, 2010

Youtube

YoutubeConclusions

1. Different ways to analyze video

2. Different units of relevation

3. Different research strategies

Different questions, one answer: methodology driven by research questions

Facebook

What you can get:- Graph API- Apps- Public Feed API & Keyword Insight API

More than 114 scientific article (Caers et al 2013)

Facebookmeta-information/external Graph enabled website

sample RQs:•Are there inconsistency between media focus and user attention?•What is the lifespan of a news?•Can the number of likes received by a movie on IMDb.com be a good predictor of the

movie's box office revenues?

references:1. Lifshits, Y. & Clara, S. EDISCOPE : SOCIAL ANALYTICS FOR ONLINE NEWS. (2010).2. Schmeh, J. Rankify – Aggregated News Ranking based on User Engagement in the Social Web. 63 (2011).

notes: this approach could be complemented by qualitative content analysis

Facebookmeta-information/pages and groups meta-information

sample RQs:•are Italian universities adopting social media to communicate and relate with students

and other strategic publics?•what is the role of Facebook in the spread of Occupy Wall Street movement?

references:1. Lovari, A. & Giglietto, F. Social Media and Italian Universities: An Empirical Study on the Adoption and Use of Facebook, Twitter and Youtube. SSRN eLibrary (Jenuary 2, 2012). Available at SSRN: http://ssrn.com/abstract=1978393 or doi:10.2139/ssrn.19783932. Caren, Neal and Gaby, Sarah, Occupy Online: Facebook and the Spread of Occupy Wall Street (October 24, 2011). Available at SSRN: http://ssrn.com/abstract=1943168 or doi:10.2139/ssrn.1943168

Facebookmeta-information/my friends personal profiles

sample RQs:•what is the level of students’ online self-disclosures on Facebook?•what my friend's most liked pages tell about me?

references:1. Kolek, E.A. & Saunders, D. Online Disclosure: An Empirical Examination of Undergraduate Facebook Profiles. Journal of Student Affairs Research and Practice 45, (2008).2. http://blog.ouseful.info/2012/01/04/social-interest-positioning-visualising-facebook-friends-likes/

Facebookmeta-information/my non-friends profiles with Facebook App

sample RQs:•what is the level of privacy awareness of Facebook users?

references:1. Rauber, G. & Almeida, V.A.F. Privacy Albeit Late. Networks 13, 26 (2011).

Facebookmeta-information/public pages and groups posts

sample RQs:•How are nonprofit organizations incorporating relationship development strategies into

their Facebook profiles?•How do groups focused on McCain versus Obama differ in terms of the frequency of

positive and negative references to candidates, the use of profanity, and references to race, religion and age?

references:1. Waters, R.D., Burnett, E., Lamm, A. & Lucas, J. Engaging stakeholders through social networking: How nonprofit organizations are using Facebook. Public Relations Review 35, 102-106 (2009).2. Woolley, J.K., Limperos, A.M. & Oliver, M.B. The 2008 Presidential Election, 2.0: A Content Analysis of User-Generated Political Facebook Groups. Mass Communication and Society 13, 631-652 (2010).

notes: this kind of study are a reasonable follow up of studies based on the analysis of pages and groups meta-information

Facebookcontents/public pages and groups posts

sample RQs:•How are nonprofit organizations incorporating relationship development strategies into

their Facebook profiles?•How do groups focused on McCain versus Obama differ in terms of the frequency of

positive and negative references to candidates, the use of profanity, and references to race, religion and age?

references:1. Waters, R.D., Burnett, E., Lamm, A. & Lucas, J. Engaging stakeholders through social networking: How nonprofit organizations are using Facebook. Public Relations Review 35, 102-106 (2009).2. Woolley, J.K., Limperos, A.M. & Oliver, M.B. The 2008 Presidential Election, 2.0: A Content Analysis of User-Generated Political Facebook Groups. Mass Communication and Society 13, 631-652 (2010).

notes: this kind of study are a reasonable follow up of studies based on the analysis of pages and groups meta-information

Facebookmeta-information/my friends posts

sample RQs:•To what extent are Facebook users using links to share information with their network

of Facebook “friends”?

references:1. Baresh, B., Knight, L., Harp, D. & Yaschur, C. Friends who choose your news: an analysis of content links on Facebook. International Symposium on Online Journalism, Austin, Texas, April 2011. (2011).

Facebookmeta-information/my friends posts

sample RQs:•To what extent are Facebook users using links to share information with their network

of Facebook “friends”?

references:1. Baresh, B., Knight, L., Harp, D. & Yaschur, C. Friends who choose your news: an analysis of content links on Facebook. International Symposium on Online Journalism, Austin, Texas, April 2011. (2011).

Notes: is such a kind of sample representative of, at last, Facebook users?

Facebookmeta-information/my non-friends posts with Facebook App

sample RQs:•To what extent are Facebook users using links to share information with their network

of Facebook “friends”?

references:

notes: this approach could be attempted in order to create a representative sample of Facebook users.

Facebookmeta-information/whole network collection

sample RQs:•What is the average number of friends in a bounded group (such as freshman)•What is the average degree of separation on Facebook or among Italian users?

references:1.2. Traud, A. & Mucha, P. Social Structure of Facebook Networks. Arxiv preprint arXiv:1102.2166 (2011).

notes: the dataset for this studies was provided by Facebook

Facebookmeta-information/partial networks collection: groups and ego networks

sample RQs:• Is there an overlap between pre-existing personal networks and Facebook network?• Is it possible to identify key local individuals by analysis Facebook network groups

structure?

references:1. Hogan, Bernie, A Comparison of On and Offline Networks through the Facebook API (December 18, 2008). Available at SSRN: http://ssrn.com/abstract=1331029 or doi:10.2139/ssrn.13310292. http://larica.uniurb.it/nextmedia/2011/11/urbino-su-facebook/

Facebookmeta-information/stream analysis

sample RQs:• Is there a correlation between number of candidate's mentions on Facebook, post

sentiment and outcomes of the elections?

references:1. http://www.politico.com/news/stories/0112/71345.html

Facebookmeta-information/sampling with Facebook

Facebook could also be used to disseminate a survey. By leveraging on Facebook advertising platform it could be possible to target the survey to specific segment of population in order to create representative sample of Facebook population (structured by gender, age and any other kind of information available in the platform). Moreover this strategy could complement the once based on Facebook App. Administering a survey via Facebook App will enable researchers to get both answers and data (age, gender, likes and other structural variables).

Facebook

Facebook

StatisticalEthnographic Computational

*****

Twitterrelevant aspects:

•Network Structure Studies: friends/follower/hubs etc.

•Users activities: messages/reTweets/@reply

•Users social practices•Emergent phenomena:

Elections, Natural disasters, Crisis communication

•Case studies (Journalism)

What you can get:- Public stream- Search API- Streaming API- Firehose data

TwitterResearchers largely used (and still use) Twitter search or streaming API.

Is the sample good enough?(Morstatter et al. 2013)

- When the number of tweets monitored increase the reliability of streaming solution decrease. - Streaming API data estimates top n hashtag when n is large but fails when n is small.- Streaming API return almost the complete set of geotagged tweets

TwitterTwitter research started within the traditional approach of network studies from a computer science perspective (Java, A. et al., 2007) and was soon followed by many researches aiming at giving a general description of the phenomenon (Huberman, B.A., Romero, D.M. & Wu, F., 2009.). The public-by-default nature of Twitter led toward a massive adoption of computational methods: data were simple, textual, and easy accessible.

Twitter

TwitterIn few years researchers started to focus on the social aspects of Twitter based interactions (Marwick, A.E. & boyd, d., 2010) and on the Twitter based emergent phenomena (Earle, P., 2010)

< Who do you tweet *to*?> No one & I love that. Or maybe myself five min. ago: I write the tweets I want to read.

I don’t tweet to anybody; I just do it to do i

TwitterIn 2011 the was a peak of interest in Twitter based research both in social sciences and in computer sciences on the following directions:- Automated analysis / event detection (Hong, L. & Davison, B.D., 2011 - Welch, M.J. et al., 2011. - Weng, J. & Lee, B.-sung, 2011)

- Events monitor and analysis (Bruns, A., 2011, Bruns, A. & Burgess, J., 2011, Rossi, L., Magnani, M. & Iadarola).- Specific case studies (Lasorsa, D., Lewis, S. & Holton, A., 2011.)

Twitter

Twitter

Twitter

Twitter

StatisticalEthnographic Computational

*****

Even for qualitative research data are usually gathered through computational methods.

Twitter

Bruns, A., 2011. How long is a tweet? Mapping dynamic conversation networks on Twitter using gawk and gephi. Information, Communication & SocietySociety, p.37-41.

Bruns, A. & Burgess, J., 2011. #Ausvotes: How twitter covered the 2010 Australian federal election. Communication, Politics & Culture, 44(2).

Dann, S., 2010. Twitter content classification. First Monday, 15(12), p.1-10.

Earle, P., 2010. Earthquake Twitter. Nature Geoscience, 3(4), p.221-222.

Go, A., Huang, L. & Bhayani, R., 2009. Sentiment Analysis of Twitter Data. Entropy, 2009(June), p.17.

Hong, L. & Davison, B.D., 2011. Predicting Popular Messages in Twitter. ReCALL, p.57-58.

Huberman, B.A., Romero, D.M. & Wu, F., 2009. Social Networks that matter: Twitter under the microscope. First Monday, 14(1).

TwitterHuberman, B.A., Romero, D.M. & Wu, F., 2009. Social Networks that matter: Twitter under the microscope. First Monday, 14(1).

Java, A. et al., 2007. Why We Twitter : Understanding Microblogging. Network, 1(ACM Press), p.56-65.

Lasorsa, D., Lewis, S. & Holton, A., 2011. Normalizing Twitter. Journalism Studies, (August), p.1-18.

Lassen, D.S. & Brown, a. R., 2010. Twitter: The Electoral Connection? Social Science Computer Review, 29(4), p.419-436.

Marwick, A.E. & boyd, d., 2010. I Tweet Honestly, I Tweet Passionately: Twitter Users, Context Collapse, and the Imagined Audience. New Media & Society, 13(1), p.114-133.

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. Proceedings of ICWSM.

Rossi, L., Magnani, M. & Iadarola, B., 2011. #rescatemineros: global media events in the microblogging age. In S. Fragoso et al., eds. Selected Papers of Internet Research.

Twitter

Tumasjan, a. et al., 2010. Election Forecasts With Twitter: How 140 Characters Reflect the Political Landscape. Social Science Computer Review, 29(4), p.402-418.

Welch, M.J. et al., 2011. Topical Semantics of Twitter Links. Time, p.327-336.

Weng, J. & Lee, B.-sung, 2011. Event Detection in Twitter. Event London, p.401-408.

Wohn, D.Y. & Na, E.K., 2011. Tweeting about TV: Sharing television viewing experiences via social media message streams. First Monday, 3(16).

TwitterWhat you can get:•user:

onameo location*o language*ofollowers/friendso lists

•messageo texto type (message, RT*, reply*)o location *o time

•network structure:onetwork of followers/friendsonetwork of conversationsonetwork of propagations

anobiiSingle research (Aiello, L.M. et al., 2012) on link creation:

creation on social ties is strongly driven by:- homophily and proximity (language, similarity of interests, geographic proximity).

Data available upon request:- user's profile- library information- groups affiliations