Social media data extraction

PLATAFORMAS DE REDES SOCIAIS:
Extração e Análise de Dados.
Janna Joceli C. de Omena
PhD candidate at UT Aus1n I Portugal (FCSH)
@jannajoceli / thesocialplaAorms.wordpress.com

Omena, 2016. Plataformas de Redes Sociais: Extração e Análise de Dados.

Conceito
Social Network Sites Social Media Platforms
n  Web Service »
n  Users Create a Profile »
Connections in the
Network [Body and Ellison, 2008]
n  Web Service »
n  Users and Third parties
» Connect and Build New
Services [Helmond, 2015]
q  Programmability
= APIs
allow applications to talk to
one another; APIs are machine-
readable interfaces [Berlind, 2015]

API Ecosystem
[Data retrieved from programmableweb.com – more than 14.590 APIs registered in February 2016. Data visualiza1on by Janna Joceli – tools: Text Ripper, Excel, Raw]

q Programmability
q Popularity
q Connectivity
q Datification
[Van Dijck and Poell, 2013]
Lógica das Redes Sociais

Linguagem da Web
Info-Web
(1.0, 2.0)
Social Web
[Tim O´Reilly]from the open web to the closed web or walled gardens of pla3orms
[O´Reilly, 2005; Dekker and Wolfsberger, 2009]
Study of:
+ proﬁles
+ friend-network mapping
+ post-demographics
Study of:
+ events, disasters,
+ elec1ons, revolu1ons and
+ social causes
Social Media Methods:
+ screen-scraped
+ crawled from mul1ple
websites
+ co-link analysis
Social Media Methods:
+ calling APIs
+ crawling
+ network analysis
+ algorithms studies
Adapted from Rogers, 2017 (forthcoming)

Gramática das Redes Sociais
Economia da atenção
[ou de likes]

+ Likes + Posts + Tweets + Retweets + Replies + Shares + Hahstags
+ Tagging + Geoloca1on + Installed Apps + Follow/Followers
‘Grammars of Action’ – Agre, 1994
‘Follow the medium’- Rogers, 2013

which “digital objects are available, how are they handled by
the device, and how can one learn from medium method, and
repurpose it for social research” (Rogers, 2015, p. 10).

Elements for cross-platform analysis - Rogers, 2017 (forthcoming)
adapted from Rieder, 2015
Elementos para análises

Front-End
Ação do U1lizador
[ex.no1ﬁcações, como alimenta a
plataforma, segngs]

Resultado do
Algoritmo
[cada plataforma tem uma base de
funcionamento]

Back-End
API
[ex.common prac1ces, rate limites,
governance]

Algoritmo
[cada plataforma tem uma base de
funcionamento]

Acesso à Informação/Dados

Social Media APIs: What to Look for?
History
Understanding the philosophy and policy
Identifying new products built + purchased by the platform
Common practices
Management of connections
Users practices
Functions
Call frequency governance
How far back in time data is made accessible?
Content moderation
Methodological issues
Data detail + Platform changes + Data reliability
Quality and representativeness of a sample
What type of data it is possible to collect?
How about lurkers?
Legal and Ethical issues
Informed consent x Anonymization
Default policy
What to Look for in Social Media APIs?

2009 2013 2014 2015 2016
Netvizz
First
time I
used
this
app
Using Netvizz to
access Facebook
data:
Personal Networks
[Friendship Connection +
Like Network]
Groups
[Open or Private]
Interactions]
Pages
[Posts by page or Posts
by page and user]
[Page like Network –
depth 1 and 2]
Using Netvizz to
access Facebook
data:
Personal Networks
Like Network]
Groups
[Open or Private]
Interactions]
Pages
by page and user]
depth 1 and 2]
Using Netvizz to access Facebook data:
:
Personal Networks
Like Network]
Groups
[Open or Private]
Interactions]
Pages
by page and user]
depth 1 and 2]
New
Limits on
the last
posts
retrieved
+
Facebook
new
Cookies
Policy

Apps + Software
Digital Methods Initiative Tools
https://wiki.digitalmethods.net/Dmi/ToolDatabase
MÉDIALAB - SciencesPo Tools
http://www.medialab.sciences-po.fr/tools/

Media Analysis [media monitoring, mapping, clouding, comparative media analysis]
Data Treatment [data collection, data analysis, information visualization]
Natively Digital [the link, the url, the tag, the domain, the PageRank, the robots.txt]
Device Centric [Google, Google imagaes, Google news, Google blog search, Yahoo, Wikipedia,
Alexa, IssueCraler, Twitter, Facebook, Amazon, iTunes, Wayback, YouTube, Instagram, Github]
Spherical[web sphere, news sphere, blogsphere, tag sphere, video sphere, image sphere, code
sphere]
Density Design - Raw
http://raw.densitydesign.org/
Bernhard Rieder – Research Software
http://labs.polsys.net/

Estratégias para Extração de Dados
q Considerar a cultura da (s) plataforma (s)
q Possibilidades e limitações = APIs e APPs
q Objectos digitais
q Delimitar plataforma (s) + query design
q Especificar período de análise
q Organizar dataset
q Definir abordagens analíticas

Abordagens Analíticas
q Critical Analytics
q Engagement Metrics
[Five metrics of engagement: dominant voice, concern,
commitment, positioning, alignment – Rogers, 19 fev 2016]
hhps://www.youtube.com/watch?v=sNwl-qGrK7M&list=PLKzQwIKtJvv_cfzQWIaVCb1H60xaeDjkL
q Network Analysis
q Statistics Summaries
q Content Analysis
[visual or textual]
q Hashtag Exploration

Facebook: Page Like Network
Omena, 2016 at hhps://thesocialplaAorms.wordpress.com/2016/07/21/facebook-page-like-network-using-ahributes-and-metrics/

Facebook: Page Like Network
» Conexões da página
[diretas e indiretas]
» Pode revelar novas conexões ou
fontes de informação
» Apresenta novas perspectivas
em relação ao posicionamento da
página [a não conexão também diz qualquer
coisa » ex. FB post id 10211579706635026 ]
» Identificar Clusters [modularity]
» Analisar popularidade/
atividade [degree] e autoridade
[pagerank]
» Debate na rede [talking about count]
» Participação do Utilizador
[a página permite que o utilizador faça
publicações? Se sim, são visíveis na timeline?]

Facebook: Page Data
» Visão geral da Página (s) e
análise dos utilizadores:
i)Resumo estatístico da reação dos
utilizadores
ii)Análise temporal das atividades
dos utilizadores e da página
» Posts e tópicos de discussão
» Análise de Comentários
[Rieder et al, 2015; Omena e Rosa, 2015]

Tumblr: Hashtag Exploration

Tumblr: Hashtag Exploration
» Co-hashtag network:
i)  Orientação sócio-política ou
representatividade cultural
ii)  Programas e anti-programas
» Debate + Localização
» Análise de conteúdo
[textual e visual]
» Categorias:
i)Principal
ii) Event-based
iii) Less popular
iv) Program x Anti-program
v) Humourous
[Omena, 2016, forthcoming]

What makes a good sample on social media?

OBRIGADA ;-)
Janna Joceli C. de Omena
PhD candidate at UT Aus1n I Portugal (FCSH)
@jannajoceli / thesocialplaAorms.wordpress.com

Social media data extraction

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