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Replication Data for: “Who reports witnessing and performing corrections on social media in the US, UK, Canada, and France?”
No full textThese are the replication materials for the article "Who reports witnessing and performing corrections on social media in the US, UK, Canada, and France?"
### Files
+ HKSMR data.tab
+ HKSMR syntax.sp
Opening up and Sharing Data from Qualitative Research: A Primer
Get PDFThis work has been funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.: 16DII111, 16DII112, 16DII113, 16DII114, 16DII115, 16DII116, 16DII117 – „Deutsches Internet-Institut“
Do “Good Citizens” fight hate speech online? Effects of solidarity citizenship norms on user responses to hate comments
Get PDFIn an effort to counter hate speech, media platforms have increasingly come to rely on ordinary users to fight abusive content. However, little is known about the predictors of this type of user engagement, which we refer to as online civic intervention (OCI). This article presents an experimental inquiry (N = 337) into whether solidarity citizenship norms promote OCI. The results show that users who support solidarity citizenship norms tend to have a greater propensity to flag hate comments and to engage in counterspeech. Overall, this indicates that “good citizens” are more inclined to stand up against hate speech online
The Language Labyrinth: Constructive Critique on the Terminology Used in the AI Discourse
No full textIn the interdisciplinary field of artificial intelligence (AI) the problem of clear terminology is especially momentous. This paper claims, that AI debates are still characterised by a lack of critical distance to metaphors like ‘training’, ‘learning’ or ‘deciding’. As consequence, reflections regarding responsibility or potential use-cases are greatly distorted. Yet, if relevant decision-makers are convinced that AI can develop an ‘understanding’ or properly ‘interpret’ issues, its regular use for sensitive tasks like deciding about social benefits or judging court cases looms. The chapter argues its claim by analysing central notions of the AI debate and tries to contribute by proposing more fitting terminology and hereby enabling more fruitful debates. It is a conceptual work at the intersection of critical computer science and philosophy of language
FAIREST Metrics and Assessment Data
No full textThis data supplements the article “FAIREST: A Framework for Assessing Research Repositories”. In the article, we introduce the FAIREST principles, an extension of the well-known FAIR principles. Along these principles, we provide comprehensive metrics for assessing and selecting solutions for building digital repositories for research artefacts. The metrics are based on two pillars:
an analysis of established features and functionalities, drawn from existing solutions,
a literature review on general requirements for digital repositories for research artefacts and related systems.
We further describe an assessment of 11 widespread solutions, with the goal to provide an overview of the current landscape of research data repository solutions, identifying gaps and research challenges to be addressed. The solutions are:
– ResearchGate
– Academia.edu
– Zenodo
– arXiv
– Bibsonomy
– Figshare
– CKAN
– DSpace
– Invenio
– Dataverse
– EPrints
Overview of the data
01 FAIREST Assessment Metrics and Solutions (All-in-one).xlsx
This Excel file includes both the assessment metrics and the results for the 11 solutions
02 FAIREST Assessment Metrics.csv
The assessment metrics as CSV
XX FAIREST Assessment XXX.csv
Assessment result for the respective solution
14 FAIREST Assessment Template.xlsx
A template to apply the metrics to an individual solution
Note: Fill in your assessment in column F and get the result at the bottom of the sheetThis research was supported by the Fundação para a Ciência e a Tecnologia through the LASIGE Research Unit, UIDB/00408/2020 and UIDP/00408/2020. This work was supported by the Federal Ministry of Education and Research of Germany (BMBF) under grant no. 16DII12 ("Deutsches Internet-Institut")
Somebody's Watching Me: Smartphone Use Tracking and Reactivity
Get PDFLike all media use, smartphone use is mostly being measured retrospectively with self-reports. This leads to misjudgments due to subjective aggregations and interpretations that are necessary for providing answers. Tracking is regarded as the most advanced, unbiased, and precise method for observing smartphone use and therefore employed as an alternative. However, it remains unclear whether people possibly alter their behavior because they know that they are being observed, which is called reactivity. In this study, we investigate first, whether smartphone and app use duration and frequency are affected by tracking; second, whether effects vary between app types; and third, how long effects persist. We developed an Android tracking app and conducted an anonymous quasi-experiment with smartphone use data from 25 people over a time span of two weeks. The app gathered not only data that were produced after, but also prior to its installation by accessing an internal log file on the device. The results showed that there was a decline in the average duration of app use sessions within the first seven days of tracking. Instant messaging and social media app use duration show similar patterns. We found no changes in the average frequency of smartphone and app use sessions per day. Overall, reactivity effects due to smartphone use tracking are rather weak, which speaks for the method's validity. We advise future researchers to employ a larger sample and control for external influencing factors so reactivity effects can be identified more reliably
Media Literacy and the Protection of Minors in the Digital Age: Intermediary initiatives during the transposition of the AVMS Directive in Spain
Get PDFThis work has been funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.: 16DII111, 16DII112, 16DII113, 16DII114, 16DII115, 16DII116, 16DII117 – „Deutsches Internet-Institut“
Bot, or not? Comparing three methods for detecting social bots in five political discourses
Get PDFSocial bots – partially or fully automated accounts on social media platforms – have not only been widely discussed, but have also entered political, media and research agendas. However, bot detection is not an exact science. Quantitative estimates of bot prevalence vary considerably and comparative research is rare. We show that findings on the prevalence and activity of bots on Twitter depend strongly on the methods used to identify automated accounts. We search for bots in political discourses on Twitter, using three different bot detection methods: Botometer, Tweetbotornot and “heavy automation”. We drew a sample of 122,884 unique user Twitter accounts that had produced 263,821 tweets contributing to five political discourses in five Western democracies. While all three bot detection methods classified accounts as bots in all our cases, the comparison shows that the three approaches produce very different results. We discuss why neither manual validation nor triangulation resolves the basic problems, and conclude that social scientists studying the influence of social bots on (political) communication and discourse dynamics should be careful with easy-to-use methods, and consider interdisciplinary research
Digidem Digest - Issue 40 (September 2021)
No full textThe Digidem Digest literature radar was a monthly curated overview of the latest publications with relevance to the research group "Democracy and Digitalization" at the Weizenbaum Institute. Their research focused around the interrelation of digitalization and democratic self-determination, asking how liberal-democratic societies appropriate digital technologies and how democracy is changing within the digital configuration. The present articles and publications were chosen by observation of leading journals within the field - a list can be found at the end of each newsletter
Digidem Digest - Issue 37 (June 2021)
No full textThe Digidem Digest literature radar was a monthly curated overview of the latest publications with relevance to the research group "Democracy and Digitalization" at the Weizenbaum Institute. Their research focused around the interrelation of digitalization and democratic self-determination, asking how liberal-democratic societies appropriate digital technologies and how democracy is changing within the digital configuration. The present articles and publications were chosen by observation of leading journals within the field - a list can be found at the end of each newsletter