Towards Hybrid Intelligence in Journalism: Findings and Lessons Learnt from a Collaborative Analysis of Greek Political Rhetoric by ChatGPT and Humans
- URL: http://arxiv.org/abs/2410.13400v1
- Date: Thu, 17 Oct 2024 09:54:54 GMT
- Title: Towards Hybrid Intelligence in Journalism: Findings and Lessons Learnt from a Collaborative Analysis of Greek Political Rhetoric by ChatGPT and Humans
- Authors: Thanasis Troboukis, Kelly Kiki, Antonis Galanopoulos, Pavlos Sermpezis, Stelios Karamanidis, Ilias Dimitriadis, Athena Vakali,
- Abstract summary: The chapter delves into various aspects of political discourse analysis, including sentiment analysis, polarization, populism, topic detection, and Named Entities Recognition (NER)
The project stands as an innovative example of human-AI collaboration within the realm of digital humanities, offering valuable insights for future initiatives.
- Score: 1.4605550954028836
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: This chapter introduces a research project titled "Analyzing the Political Discourse: A Collaboration Between Humans and Artificial Intelligence", which was initiated in preparation for Greece's 2023 general elections. The project focused on the analysis of political leaders' campaign speeches, employing Artificial Intelligence (AI), in conjunction with an interdisciplinary team comprising journalists, a political scientist, and data scientists. The chapter delves into various aspects of political discourse analysis, including sentiment analysis, polarization, populism, topic detection, and Named Entities Recognition (NER). This experimental study investigates the capabilities of large language model (LLMs), and in particular OpenAI's ChatGPT, for analyzing political speech, evaluates its strengths and weaknesses, and highlights the essential role of human oversight in using AI in journalism projects and potentially other societal sectors. The project stands as an innovative example of human-AI collaboration (known also as "hybrid intelligence") within the realm of digital humanities, offering valuable insights for future initiatives.
Related papers
- Artificial Intelligence and Journalism: A Systematic Bibliometric and Thematic Analysis of Global Research [0.51795041186793]
This study presents a comprehensive systematic review of published articles on AI in journalism from 2010 to 2025.<n>The findings show a sharp increase in research activity after 2020, with prominent focus areas including automation, misinformation, and ethical governance.<n>The review also highlights regional disparities in scholarly contributions, with limited representation from the Global South.
arXiv Detail & Related papers (2025-07-15T01:11:39Z) - The Narrative Construction of Generative AI Efficacy by the Media: A Case Study of the Role of ChatGPT in Higher Education [1.3264707875439612]
This study examines how U.S. news media construct narratives about the efficacy of generative AI (GenAI)<n>Our findings identify six key topics in the media discourse, with sentiment analysis revealing generally positive portrayals of ChatGPT's integration into higher education.<n>In contrast, media narratives express more negative sentiment regarding their impact on entry-level jobs and college admissions.
arXiv Detail & Related papers (2025-07-12T10:19:50Z) - Exploring Societal Concerns and Perceptions of AI: A Thematic Analysis through the Lens of Problem-Seeking [0.0]
This study introduces a novel conceptual framework distinguishing problem-seeking from problem-solving to clarify the unique features of human intelligence in contrast to AI.<n>The framework emphasizes that while AI excels at efficiency and optimization, it lacks the orientation derived from grounding and the embodiment flexibility intrinsic to human cognition.
arXiv Detail & Related papers (2025-05-29T18:24:34Z) - AgoraSpeech: A multi-annotated comprehensive dataset of political discourse through the lens of humans and AI [1.3060410279656598]
AgoraSpeech is a meticulously curated, high-quality dataset of 171 political speeches from six parties during the Greek national elections in 2023.
The dataset includes annotations (per paragraph) for six natural language processing (NLP) tasks: text classification, topic identification, sentiment analysis, named entity recognition, polarization and populism detection.
arXiv Detail & Related papers (2025-01-09T18:17:59Z) - Political-LLM: Large Language Models in Political Science [159.95299889946637]
Large language models (LLMs) have been widely adopted in political science tasks.
Political-LLM aims to advance the comprehensive understanding of integrating LLMs into computational political science.
arXiv Detail & Related papers (2024-12-09T08:47:50Z) - Artificial Intelligence in Brazilian News: A Mixed-Methods Analysis [0.0]
This study analyzes 3,560 news articles from Brazilian media published between July 1, 2023, and February 29, 2024, from 13 popular online news outlets.
The findings reveal that Brazilian news coverage of AI is dominated by topics related to applications in the workplace and product launches.
The analysis also highlights a significant presence of industry-related entities, indicating a strong influence of corporate agendas in the country's news.
arXiv Detail & Related papers (2024-10-22T20:52:51Z) - Aligning AI with Public Values: Deliberation and Decision-Making for Governing Multimodal LLMs in Political Video Analysis [48.14390493099495]
How AI models should deal with political topics has been discussed, but it remains challenging and requires better governance.<n>This paper examines the governance of large language models through individual and collective deliberation, focusing on politically sensitive videos.
arXiv Detail & Related papers (2024-09-15T03:17:38Z) - Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions [67.60397632819202]
Building socially-intelligent AI agents (Social-AI) is a multidisciplinary, multimodal research goal.
We identify a set of underlying technical challenges and open questions for researchers across computing communities to advance Social-AI.
arXiv Detail & Related papers (2024-04-17T02:57:42Z) - Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice [63.20307830884542]
Next several decades may well be a turning point for humanity, comparable to the industrial revolution.
Launched a decade ago, the project is committed to a perpetual series of studies by multidisciplinary experts.
We offer ten recommendations for action that collectively address both the short- and long-term potential impacts of AI technologies.
arXiv Detail & Related papers (2024-04-06T22:18:31Z) - Human participants in AI research: Ethics and transparency in practice [0.9608936085613567]
Research involving human participants has been critical to advances in artificial intelligence (AI) and machine learning (ML)
Yet AI and participatory researchers lack guidelines for ethical research with human participants in AI and ML.
This paper seeks to address these concerns and position technical researchers with practical knowledge for their work.
arXiv Detail & Related papers (2023-11-02T14:12:21Z) - Mapping AI Arguments in Journalism Studies [0.0]
This study investigates and suggests typologies for examining Artificial Intelligence (AI) within the domains of journalism and mass communication research.
We aim to elucidate the seven distinct subfields of AI, which encompass machine learning, natural language processing (NLP), speech recognition, expert systems, planning, scheduling, optimization, robotics, and computer vision.
arXiv Detail & Related papers (2023-09-03T05:04:11Z) - PAR: Political Actor Representation Learning with Social Context and
Expert Knowledge [45.215862050840116]
We propose textbfPAR, a textbfPolitical textbfActor textbfRepresentation learning framework.
We retrieve and extract factual statements about legislators to leverage social context information.
We then construct a heterogeneous information network to incorporate social context and use relational graph neural networks to learn legislator representations.
arXiv Detail & Related papers (2022-10-15T19:28:06Z) - Sentiment Analysis of Political Tweets for Israel using Machine Learning [0.0]
This research proposes an analytical study using Israeli political Twitter data to interpret public opinion towards the Palestinian-Israeli conflict.
The attitudes of ethnic groups and opinion leaders in the form of tweets are analyzed using Machine Learning algorithms.
arXiv Detail & Related papers (2022-04-12T12:07:43Z) - Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and
Stir" [76.44130385507894]
This paper aims to ground what we dub a 'participatory turn' in AI design by synthesizing existing literature on participation and through empirical analysis of its current practices.
Based on our literature synthesis and empirical research, this paper presents a conceptual framework for analyzing participatory approaches to AI design.
arXiv Detail & Related papers (2021-11-01T17:57:04Z) - Human-Robot Collaboration and Machine Learning: A Systematic Review of
Recent Research [69.48907856390834]
Human-robot collaboration (HRC) is the approach that explores the interaction between a human and a robot.
This paper proposes a thorough literature review of the use of machine learning techniques in the context of HRC.
arXiv Detail & Related papers (2021-10-14T15:14:33Z) - Empowering Local Communities Using Artificial Intelligence [70.17085406202368]
It has become an important topic to explore the impact of AI on society from a people-centered perspective.
Previous works in citizen science have identified methods of using AI to engage the public in research.
This article discusses the challenges of applying AI in Community Citizen Science.
arXiv Detail & Related papers (2021-10-05T12:51:11Z) - The State of AI Ethics Report (Volume 5) [0.0]
Report focuses on AI ethics with a special emphasis on "Environment and AI", "Creativity and AI", and "Geopolitics and AI"
Special contributions on the subject of pedagogy in AI ethics, sociology and AI ethics, and organizational challenges to implementing AI ethics in practice.
Report also has an extensive section covering the gamut of issues when it comes to the societal impacts of AI.
arXiv Detail & Related papers (2021-08-09T10:47:14Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.