We have released CooRTweet version 2.0. This version revises the approach, fixes some bugs, and introduces new features. The package and introductory vignette can be found on CRAN: https://cran.r-project.org/web/packages/CooRTweet.
I have uploaded the materials for my Advanced Data Analysis course on Mediation and Moderation online. The instructional material can be found at this link. It is based on the excellent book of Andrew F. Hayes Introduction to Mediation, Moderation, and Conditional Process Analysis, an invaluable resource to learn these techniques, written with rare clarity. The material includes a brief introduction to R and RStudio, a short summary of exploratory data analysis and linear regression, and sections dedicated to mediation, moderation, and mediated moderation using the Hayes’ process software.
I quickly checked the impact of the Facebook MisinformationPolicy (announced on March 7, 2019) on the endorsements of vaccine-related posts by Italian misinformation actors, employing interrupted time series analysis (you can read about this technique in the didactic material I have made available online at https://nicolarighetti.github.io/Time-Series-Analysis-With-R/).
There is a small instantaneous drop in likes, a slight inversion in the overall trend, and a persistent decrease in the average likes from before to after the policy implementation. The analysis is just exploratory and has several limitations (e.g., small sample size), but the effect looks clear.
The analysis is directly inspired by the recent paper of Gu et al. It is, in fact, a quick check of their findings in the Italian context: Gu, J., Dor, A., Li, K., Broniatowski, D. A., Hatheway, M., Fritz, L., & Abroms, L. C. (2022). The impact of Facebook’s vaccine misinformation policy on user endorsements of vaccine content: An interrupted time series analysis. Vaccine, 40(14), 2209-2214.
The Facebook accounts spreading misinformation that I employed in the analysis come from the MINE project: Giglietto, F., Farci, M., Marino, G., Mottola, S., Radicioni, T., & Terenzi, M. (2022, January 7). Mapping Nefarious Social Media Actors to Speed-up Covid-19 Fact-checking. https://lnkd.in/eRMzrrvP
As part of the CHANSE initiative, the Austrian Science Fund (FWF) financed (about 300,000€) the project “PolarVis: Visual Persuasion in a Transforming Europe” (2023-2026) led by Annie Waldherr (PI) and Nicola Righetti (co-PI).
Climate change has been called the defining crisis of our time. In the last few years, millions of people have taken to the streets to demand urgent action on the escalating ecological emergency. Social media have had great importance in the development of the movement. For example, the virality of posts on Twitter and Instagram has quickly transformed the activist Greta Thunberg into an iconic figure, attracting supportive but also openly hostile reactions. The importance of images in the online communication of the movement and the emotions moving these activists and those who attack them online draw attention to the symbolic and emotional role of images for social movements. The PolarVis project will examine the role of visual content in processes of political polarization and belonging in the digital age by focusing on the intergenerational issue of climate change and the green transition.
PolarVis: Visual persuasion in a transforming Europe: The affective and polarizing power of visual content in online political discourse will be led by Annie Waldherr (PI) and Nicola Righetti (Co-PI), and supported by a postdoctoral researcher as well as a student research assistant. The funding provided by the Austrian Science Fund (FWF) totals to around € 300.000 over the course of the next three years. The Viennese project of PolarVis is part of a large and interdisciplinary international consortium within the CHANSE initiative. The consortium is led by Alexandra Segerberg of the Department of Government at Uppsala Universitet, Sweden.
Further information on the project can be accessed here.
Update: this post refers to the first versions of the package CooRTweet, which is now a multi platform package for coordinated behavior analysis. Read more here.
I have just release the beta version of CooRTweet, an R package that I developed to help detecting coordinated networks on Twitter.
The CooRTweet package builds on the existing literature on coordinated behavior and the experience of previous software, particularly CooRnet, to provide R users with an easy-to-use tool for coordinated action detection.
Coordinated behavior is a relevant social media strategy employed for political astroturfing (Keller et al., 2020), the spread of inappropriate content online (Giglietto et al., 2020), and activism. Software for academic research and investigative journalism has been developed in the last few years to detect coordinated behavior, such as the CooRnet R package (Giglietto, Righetti, Rossi, 2020), which detects Coordinated Link Sharing Behavior (CLSB) and Coordinated Image Sharing on Facebook and Instagram (CooRnet website), and the Coordination Network Toolkit by Timothy Graham (Graham, QUT Digital Observatory, 2020), a command line tool for studying coordination networks in Twitter and other social media data. CooRTweet adds to this set of tools with an easy app for R users.
Further details and the instruction for installing and using the package are available on GitHub: https://github.com/nicolarighetti/CooRTweet
The report of the research project MINE-GE: Mapping Coordinated Inauthentic Behavior in the Lead Up to the 2021 German Federal Election has been released. During the project, which was funded by Landesanstalt für Medien Nordrhein Westfalen, we collected over 13,000 Facebook Ads, 2.5 million political posts, and 1.8 Million URLs shared on Facebook, Twitter, and Instagram by parties, candidates, and other social media users in the six weeks up to the election day, to monitor political social media communication, detect coordinated networks and analyze possible micro-targeting strategies.
The report is available in English and German on the website of Landesanstalt für Medien Nordrhein Westfalen at the following links:
- English version: Righetti, N., Giglietto, F., Kakavand, A.E., Kulichkina, A., Marino, G., Terenzi, M. (2022). POLITICAL ADVERTISEMENT AND COORDINATED BEHAVIOR ON SOCIAL MEDIA IN THE LEAD-UP TO THE 2021 GERMAN FEDERAL ELECTIONS.
- German version: Righetti, N., Giglietto, F., Kakavand, A.E., Kulichkina, A., Marino, G., Terenzi, M. (2022). POLITISCHE WERBUNG UND KOORDINIERTES VERHALTEN IN SOZIALEN MEDIEN IM VORFELD DER BUNDESTAGSWAHL 2021.
The Anti-Gender Debate on Social Media. A Computational Communication Science Analysis of Networks, Activism, and Misinformation (which can be freely accessed at this link) takes into account 10 years of anti-gender communication on Facebook in Italy, and proposes a multifaceted analysis of different aspects of the debate, including activism and misinformation.
It shows that both right-wing/populists/religious and pro-LGBTQI+ actors were involved in the debate, but the former got more engagement. Notably, religious accounts got even more engagement than the right-wing ones. Also, posts from left-wing parties’ accounts were just a few.
The most engaging posts against Gender came from Radio Maria, a popular (and sometimes controversial) catholic radio, and the conversations peaked in 2015, close to the conservative manifestation “Family Day”, but religious actors have kept paying attention to the issue.
Time series analysis suggested that Facebook posts mostly amplified an agenda set by news media following offline events. Similarly, Facebook has been used to amplify “traditional” types of activism, like petitions “against gender”.
However, an analysis through CooRnet also revealed the presence of coordinated Facebook networks spreading news stories on gender ideology, also coming from websites renowned for spreading misinformation and low-quality, click-bait news stories.
Still on the subject of misinformation, the analysis shows that 2% of the about 20,000 analyzed Facebook posts associated LGBTQI+ people and organizations with paedophilia by means of “gender ideology”.
A new paper briefly reviewing the scientific literature on fake news published up to 2020 is online on First Monday. You can read it here: Four Years of Fake News. A Quantitative Analysis of the Scientific Literature
Introduction: Since 2016, “fake news” has been the main buzzword for online misinformation and disinformation. This term has been widely used and discussed by scholars, leading to hundreds of publications in a few years. This report provides a quantitative analysis of the scientific literature on the topic published up to 2020.
Methods: Documents mentioning the keyword “fake news” have been searched in Scopus, a large multidisciplinary scientific database. Frequency analysis of metadata and automated lexical analysis of titles and abstracts have been employed to answer the research questions.
Results: 2,368 scientific documents mentioned “fake news” in the title or abstract, published by 5,060 authors and 1,225 sources. Until 2016 the number of documents mentioning the term was less than 10 per year, suddenly rising from 2017 (203 documents), and steadily increasing in the following years (477 in 2018, 694 in 2019, and 951 in 2020). Among the most prolific countries are the USA and European countries such as the UK, but also many non-Western countries such as India and China. Computer Science and Social Sciences are the disciplinary fields with the largest number of documents published. Three main thematic areas emerged: computational methodologies for fake news detection, the social and individual dimension of fake news, and fake news in the public and political sphere. There are 10 documents with more than 200 citations, and two papers with a record number of citations (Alcott & Gentzkow, 2017; Lazer et al., 2018).
Conclusions: Research on “fake news” keeps on the rise, with a marked upward trend following the 2016 USA Presidential election. Despite having been the subject of debate and also criticism, the term is still widely used. A strong methodological interest in fake news detection through machine learning algorithms emerged, which – it can be argued – can be profitably balanced by a social science approach able to unpack the phenomenon also from a qualitative and theoretical point of view. Although dominated by the USA and other Western countries, the research landscape includes different countries of the world, thus enabling a wider and more nuanced knowledge of the problem. A constantly growing field of study like the one concerning fake news requires scholars to have a general overview of the scientific productions on the topic, and systematic literature reviews can be of help. The variety of perspectives and topics addressed by scholars also means that future analyses will need to focus on more specific topics.
I have recently started to teach a course in data analysis with R at the University of Vienna, and I am creating a free online book where I explain fundamental R functions and data analysis operations, with a specific focus on time series analysis.
I’ll update the online book as the course goes on, but some chapters are already online. You can read the book at this link: Time Series Analysis With R
A new paper (open access!) is out: Digital Animal Advocacy: A Study on Facebook Communication Styles of Italian Animal Rights Organizations and their Followers’ Reactions.
The paper analyzes the Facebook communication of the Italian galaxy of Italian animal advocates by using a text-mining approach, and reflects on the role of social media in promoting specific political approaches to animal rights.
The social media ecology does not change or construct the different positions of different sectors of animal advocacy, but contributes to amplify their distances, favoring the visibility or, using the term adopted by Dijck and Poell (2013), the ‘popularity’ of some groups over others. It is no coincidence that mainstream AAOs, which have greater financial and professional resources at their disposal, also have Facebook pages with the highest number of followers (Tab. 3), nor that they are clearly fully aware of the possibilities of exploiting the algorithms that preside over the distribution of the most popular content (…) in order to hack the social media attention economy (…) by calling on the concerted efforts of well-organized armies of web-activists.
From this perspective, Italian animal advocacy reflects a lack of democracy in digital platforms and is a further proof of the adage ‘the rich get richer and the poor get poorer’ (Merton, 1968). At least for the moment, the horizontal and democratic nature of Internet-based communication that is hoped for (in the case of anarchist AAOs) or explicitly claimed as already existent and widespread (in the case of anti-political AAOs) is absent (…)