Yarden Skop
Biographic Data
| ID | 376780 |
|---|---|
| NAME | Yarden Skop |
| GIVEN NAMES | Yarden |
| FAMILY NAME | Skop |
| SIGNATURE | SKOP Y |
| AFFILIATIONS | University of Siegen |
| ORCID | 0000-0001-7833-9811 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 7 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Between fact and fairy: Tracing the hallucination metaphor in AI discourse
Large and powerful language models such as OpenAI’s GPT model family, Google’s LaMDA and BERT or Meta’s LlaMA are integral to many applications, such as translation, summarization or language generation. They have become an inherent part of current everyday activities and working practices. These models produce and process language in an impressively convincing human-like manner, but also repeatedly generate outputs that appear untrustworthy and …
How Fact-Checkers Are Becoming Machine Learners: A Case of Meta’s Third Party Programme
A recent development in the field of fact-checking is what some scholars call the “debunking turn” in which fact-checking organisations move from fact-checking expressions of politicians and public figures to checking claims made on social media. A main driver of this change is the proliferation of a paid program initiated by Meta, where fact-checkers check and label claims on the platform in exchange for monetary remuneration. This paper draws o…
Opaque algorithms, transparent biases: Automated content moderation during the Sheikh Jarrah Crisis
Social media platforms, while influential tools for human rights activism, free speech, and mobilization, also bear the influence of corporate ownership and commercial interests. This dual character can lead to clashing interests in the operations of these platforms. This study centers on the May 2021 Sheikh Jarrah events in East Jerusalem, a focal point in the Israeli-Palestinian conflict that garnered global attention. During this period, Pales…
How should platforms be archived? On sustainable use practices of a Telegram Archive to study Russia’s war against Ukraine
After Russia’s war against Ukraine destroyed people’s ability to move and communicate freely in Ukraine, many Ukrainians turned to social media and messenger apps, especially Telegram, to produce and share information. The vast amount of this digital data is privatized, ephemeral, and difficult to utilize for research, raising urgent questions about its sustainable accessibility and usability. In this article, we explore a specific aspect of digi…
The fabrics of machine moderation: Studying the technical, normative, and organizational structure of Perspective API
Over recent years, the stakes and complexity of online content moderation have been steadily raised, swelling from concerns about personal conflict in smaller communities to worries about effects on public life and democracy. Because of the massive growth in online expressions, automated tools based on machine learning are increasingly used to moderate speech. While 'design-based governance' through complex algorithmic techniques has come under i…
The fabrics of machine moderation: Studying the technical, normative, and organizational structure of Perspective API
Over recent years, the stakes and complexity of online content moderation have been steadily raised, swelling from concerns about personal conflict in smaller communities to worries about effects on public life and democracy. Because of the massive growth in online expressions, automated tools based on machine learning are increasingly used to moderate speech. While 'design-based governance' through complex algorithmic techniques has come under i…
How should platforms be archived? On sustainable use practices of a Telegram Archive to study Russia’s war against Ukraine
After Russia’s war against Ukraine destroyed people’s ability to move and communicate freely in Ukraine, many Ukrainians turned to social media and messenger apps, especially Telegram, to produce and share information. The vast amount of this digital data is privatized, ephemeral, and difficult to utilize for research, raising urgent questions about its sustainable accessibility and usability. In this article, we explore a specific aspect of digi…
The fabrics of machine moderation: Studying the technical, normative, and organizational structure of Perspective API
Over recent years, the stakes and complexity of online content moderation have been steadily raised, swelling from concerns about personal conflict in smaller communities to worries about effects on public life and democracy. Because of the massive growth in online expressions, automated tools based on machine learning are increasingly used to moderate speech. While 'design-based governance' through complex algorithmic techniques has come under i…
Opaque algorithms, transparent biases: Automated content moderation during the Sheikh Jarrah Crisis
Social media platforms, while influential tools for human rights activism, free speech, and mobilization, also bear the influence of corporate ownership and commercial interests. This dual character can lead to clashing interests in the operations of these platforms. This study centers on the May 2021 Sheikh Jarrah events in East Jerusalem, a focal point in the Israeli-Palestinian conflict that garnered global attention. During this period, Pales…
How should platforms be archived? On sustainable use practices of a Telegram Archive to study Russia’s war against Ukraine
After Russia’s war against Ukraine destroyed people’s ability to move and communicate freely in Ukraine, many Ukrainians turned to social media and messenger apps, especially Telegram, to produce and share information. The vast amount of this digital data is privatized, ephemeral, and difficult to utilize for research, raising urgent questions about its sustainable accessibility and usability. In this article, we explore a specific aspect of digi…
How Fact-Checkers Are Becoming Machine Learners: A Case of Meta’s Third Party Programme
A recent development in the field of fact-checking is what some scholars call the “debunking turn” in which fact-checking organisations move from fact-checking expressions of politicians and public figures to checking claims made on social media. A main driver of this change is the proliferation of a paid program initiated by Meta, where fact-checkers check and label claims on the platform in exchange for monetary remuneration. This paper draws o…
Between fact and fairy: Tracing the hallucination metaphor in AI discourse
Large and powerful language models such as OpenAI’s GPT model family, Google’s LaMDA and BERT or Meta’s LlaMA are integral to many applications, such as translation, summarization or language generation. They have become an inherent part of current everyday activities and working practices. These models produce and process language in an impressively convincing human-like manner, but also repeatedly generate outputs that appear untrustworthy and …
Computer Science (4 works) · Artificial Intelligence (2 works) · Ethics and Social Impacts of AI (2 works) · Hate Speech and Cyberbullying Detection (2 works) · Machine learning (2 works) · Moderation (2 works) · Political science (2 works) · Psychology (2 works) · Adversarial Robustness in Machine Learning (1 works) · Algorithm (1 works)