research question

5—How does the discussion about Hate Speech & Filtering develop on the web?

Authorities mentioned by the platforms using the “Censorship” query Platform Authorities mentioned by the platforms using the “Filtering” query Legend Nadine Strossen U.S. Germany Twitter Google Facebook College students NCAC Islam Christianity American campus New Scientist UK universities Leftist Cambrige University Press Jeremy Waldron Reddit Yale News James Kirchirk Yale University University of Minnesota Hays Code FCC Black people American Police Alex Jones Sweden EU The Washington Post Gab Microsoft IT companies TNW Eventbrite Scottish Pen FAC Richard Spencer Georgetown University BBC ACLU ACLU University DELL Technologies Figueiredo Daniel Faltesek GT&T Instagram CBS News Nick Thompson Council of Europe Swiss Institute of Comparative Law CDT House Judiciary Committee INHOPE Bricks Project Article 19 Universal Declaration of Human Rights Inversoft Clean Speak Semantic Scholar Perceptron algorithm Relaxed Online SVM algorithm Vindicator Cambridge Analytica Gamergate EA Kate Hansen France ACMS Mestiça Legal Zoom YouTube CRT COSPE Japan United Nations Court of Justice of the European Union (CJEU) Austrian Supreme Court The New York Times ALA Center for American progress NC JOLT Montana professor Quora NPR University of Washington Brookings Stanford University U.S. The Washington Times Handelsbatt Global The Economist Wikipedia Project Syndicate Two Hat Security The Conversation Germany LSE Media Policy Project Politico The Hollywood Reporter UC Santa Barbara LSE Media Policy Project Wharton University Silicon Valley Watcher Huff Post The Guardian Politico Reuters Twitter The Rubin Report Ripon Collage Reason Nadine Strossen Knight First Amendament Institute The Atlantic Cato Institute Daily Beast Index Oxford University Press Amazon Usa Today The Cornell University NPR University of Washington Brookings EFF Wharton University Politico Daily Mirror Forbes OSCE AdHugger Stanford University Silicon Valley Watcher The Washington Times Huff Post Quartz Financial Express Snopes CBS Tampa Bay EDRI The Telegraph Venture Beat Battle of ideas TED Fortune Wired The Globe and Mail Variety Futurism Gizmodo Handelsbatt Global Reuters Wharton University Politico The Washington Times Silicon Valley Watcher The Guardian Liberties EFF Daily Mirror Fb's user Mic Two Hat Security The Conversation Fb's user U.S. The New York Times ALA Center for American progress NC JOLT Montana professor Quora University of Washington NPR Brookings Stanford University The Washington Times The Conversation Germany LSE Media Policy Project Politico Handelsbatt Global The Economist Wikipedia Project Syndicate Two Hat Security Wharton University Silicon Valley Watcher Huff Post The Guardian Politico Reuters Twitter The Hollywood Reporter LSE Media Policy Project UC Santa Barbara The Rubin Report Ripon Collage Reason Nadine Strossen Knight First Amendament Institute The Atlantic Cato Institute Daily Beast Index Oxford University Press Amazon Usa Today The Cornell University NPR University of Washington Google Brookings EFF Wharton University Politico Daily Mirror Forbes OSCE AdHugger Stanford University Silicon Valley Watcher The Washington Times Facebook Huff Post Quartz Financial Express Snopes CBS Tampa Bay EDRI The Telegraph Venture Beat Battle of ideas TED Fortune Wired The Globe and Mail Variety Futurism Gizmodo Handelsbatt Global Reuters Wharton University Politico The Washington Times Silicon Valley Watcher The Guardian Liberties EFF Daily Mirror Mic Two Hat Security The Conversation
Description Protocol Data

Description

This last visualization highlights the important role that the major IT companies—Facebook, Google and Twitter—play in the Hate Speech & Filtering discussion, since during the analysis it has become clear that they are often accused of censorship of contents. Also Germany and US stand out from the visualization, because of their different legislative conducts and mindsets regarding Hate Speech, which often causes discussions on the theme. Finally, the figure of Nadine Strossen emerges, a writer who supports the idea that Hate Speech needs to be tackled with Free Speech and not censorship.

Considering these conclusions and the opinions emerged in the previous protocols, we can deduce that the discussion is far more complex and has much broader boundaries than what we expected, underlining the fundamental question that the Hate Speech controversy generates: who should have the responsability and the power to regulate what may or may not be said online?

Indeed, the aim of this last protocol was to produce a visual that showed which platforms deal with the Hate Speech topic, whether they speak in terms of filtering or censorship and, above all, who are the main actors in the conversation, i.e. those who are asked to take a position, those who have the power to act and bear the weight of judgment from the internet community.

The sites that express themselves on the subject have been represented with black strokes around the relative nodes. In order not to lose the controversial value of the discussion the color of the edges that originate from the platform is painted with blue if the type of speech was about filtering and orange if instead it was about censorship. The arrows lead to those who are mentioned in the speech, those spoken of. The radius of the circumferences derives from the number of times they have been mentioned, while the color depends in percentage if they have been mentioned regarding filtering or censorship. The toggles on the left help to highlight the connections between the nodes.

Protocol

As a first step we wanted to discover what users could find on Wikipedia about filtering methods, but we discovered that there isn’t an existing Wikipedia page about this topic, so we had to search for information in a different way. We browsed Google privately in Incognito mode with Firefox and we analyzed the topic with two different queries: “Hate Speech & Filtering” and “Hate Speech & Censorship”. We decided to use both queries because there is a controversy between the two terms: “Filtering” itself has a positive connotation but there are people who believe that it is only a nice way to censor contents.

We created an Excel file where we started to collect the first 50 results for both queries, reporting also the Google rank. After this first step, we analyzed the structure of every site and we collected information about the actors which shared the content, the date in which the content was posted online and the sites typology according to WebPulse Site Review tool.

After these sites’ categorization, we analyzed what are the most frequents words used in each site according to Voyant Tools. We compared the obtained results with a manual research on the site, paying attention to the title of each article to underline what are the most important authorities in the debate and also the most shared opinions.

Data

Data Source: WebPulse Site Review tool, Voyant Tools
Timestamp: 10/31/2018
View Data (34 KB)