UniTO/anno3/avrc/assignments/dataviz/slides/index.html

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2019-12-05 16:44:41 +01:00
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<title>Datavisualization</title>
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<h1>Data Visualization</h1>
<h3>Quantify Social Media Usage from mainstream Politicians</h3>
<p>
<small>by <a href="http://fragal.eu">Francesco Gallà</a> and <a href="https://francescomecca.eu">Francesco Mecca</a></small>
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Social media played a significant role facilitating communication and interaction among *socially-aware* communities and participants of political protests.
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People used social media to organize demonstrations (both pro- and anti-governmental), disseminate information about their activities, and raise local and global awareness of ongoing events
E.g. &#x2193;
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<img src="/img/arab.jpg" alt="HTML5 Doctor Logo" />
<p>
<a href="http://pircenter.org/kosdata/page_doc/p2594_2.pdf"><small>Stepanova, Ekaterina: "The Role of Information Communication Technologies in the "Arab Spring"</small></a> </p>
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<img src="/img/hong.jpg" alt="HTML5 Doctor Logo" />
<a href="https://www.nytimes.com/2019/09/17/opinion/hong-kong-protest.html"><small>
Hong Kong protest in 2019</small></a>
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<p>
In recent years mainstream politicians strengthen their presence in social media platforms, recognizing the power of such tools.</p>
<a href="https://mashable.com/2012/10/02/voter-suppression-social-media/?europe=true">
<img src="https://www.bing.com/th?id=OIP.ckLaqp18dHXFMK-3064CsQHaEK&pid=Api&rs=1"/></a>
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## Our Objective
Quantify and present data on two italian politicians, **Matteo Renzi** and **Matteo Salvini** as a first step towards an appropriate study of the behaviour of influencial politicians online.
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## Dataset
Our dataset consisted in 5370 posts by Matteo Renzi and Matteo Salvini publicly accessible on Facebook.
The dataset was obtained by scraping using [python requests](https://2.python-requests.org/en/master/).
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## Main Difficulties
Scraping Facebook is a hard task if you can't request API keys.
* We got banned various times
* Page elements related to likes, interactions and responding users always change `id` and `class`
For these reasons we limited the analysis to just two politicians.
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* page created in September 2009
* 959 posts from 01-01-2018 to 24-11-2019
* Posts from 2009 to 2017 were removed by the owner of the page
* In total 79 000 € were spent on advertising the page on Facebook
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<section data-background="img/salvini.jpg" data-markdown>
* page created in February 2013
* 4411 posts from 28-02-2013 to 24-11-2019
* In total 164 000 € were spent on advertising the page on Facebook
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## Future improvements
Consider that a post could provide different values such as:
* increase partecipation
* provide information
* grab or detract attention
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## Future improvements
Focus on semantic analysis:
* geographical data
* number of likes, shares
* rate of engagement
* sentiment analysis
* fake news detection
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## Network Perspective
Model the analysis from an ego network:
* profiles of people following a politician
* spread of relevant/fake information
* model engagement and cascading behaviour with other users
* model social influence
* understand esternalities on a macro scale
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<h1>Thank you!</h1>
<p><small><a href="#/16">but if you really want more...</a></small></p>
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