How ChatGPT Changed the Media's Narratives on AI: A Semi-Automated Narrative Analysis Through Frame Semantics

• URL: http://arxiv.org/abs/2408.06120v1
• Date: Mon, 12 Aug 2024 13:02:31 GMT
• Title: How ChatGPT Changed the Media's Narratives on AI: A Semi-Automated Narrative Analysis Through Frame Semantics
• Authors: Igor Ryazanov, Carl Öhman, Johanna Björklund,
• Abstract summary: We perform a mixed-method frame-based analysis on a dataset of more than 49,000 sentences collected from 5 news articles that mention AI. During this period discourse has become increasingly centred around experts and political leaders. A deeper shift of the data suggests the types of threat AI is thought to represent, as well as the qualities of it.
• Score: 0.25822445089477464
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The recent explosion of attention to AI is arguably one of the biggest in the technology's media coverage. To investigate the effects it has on the discourse, we perform a mixed-method frame semantics-based analysis on a dataset of more than 49,000 sentences collected from 5846 news articles that mention AI. The dataset covers the twelve-month period centred around the launch of OpenAI's chatbot ChatGPT and is collected from the most visited open-access English-language news publishers. Our findings indicate that during the half year succeeding the launch, media attention rose tenfold$\unicode{x2014}$from already historically high levels. During this period, discourse has become increasingly centred around experts and political leaders, and AI has become more closely associated with dangers and risks. A deeper review of the data also suggests a qualitative shift in the types of threat AI is thought to represent, as well as the anthropomorphic qualities ascribed to it.

Related papers

• From tools to thieves: Measuring and understanding public perceptions of AI through crowdsourced metaphors [1.2461369993945386]
  We identify 20 dominant metaphors shaping public understanding of AI. We find that Americans generally view AI as warm and competent. These implicit perceptions, along with the identified dominant metaphors, strongly predict trust in and willingness to adopt AI.
  arXiv  Detail & Related papers  (2025-01-29T23:17:43Z)
• Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media [38.99664377299462]
  Social media platforms are experiencing a growing presence of AI-Generated Texts (AIGTs) Despite its importance, a systematic study to assess the prevalence of AIGTs on social media is still lacking. This paper aims to quantify, monitor, and analyze the AIGTs on online social media platforms.
  arXiv  Detail & Related papers  (2024-12-24T04:04:54Z)
• Human Bias in the Face of AI: The Role of Human Judgement in AI Generated Text Evaluation [48.70176791365903]
  This study explores how bias shapes the perception of AI versus human generated content. We investigated how human raters respond to labeled and unlabeled content.
  arXiv  Detail & Related papers  (2024-09-29T04:31:45Z)
• Artificial Intelligence Index Report 2024 [15.531650534547945]
  The AI Index report tracks, collates, distills, and visualizes data related to artificial intelligence (AI) The AI Index is recognized globally as one of the most credible and authoritative sources for data and insights on AI. This year's edition surpasses all previous ones in size, scale, and scope, reflecting the growing significance that AI is coming to hold in all of our lives.
  arXiv  Detail & Related papers  (2024-05-29T20:59:57Z)
• Mapping ChatGPT in Mainstream Media to Unravel Jobs and Diversity Challenges: Early Quantitative Insights through Sentiment Analysis and Word Frequency Analysis [0.0]
  This article presents a quantitative data analysis of the early trends and sentiments revealed by conducting text mining and NLP methods. The findings revealed in sentiment analysis, ChatGPT and artificial intelligence, were perceived more positively than negatively in the mainstream media. This article is a critical analysis into the power structures and collusions between Big Tech and Big Media in their hegemonic exclusion of diversity and job challenges from mainstream media.
  arXiv  Detail & Related papers  (2023-05-25T15:10:51Z)
• A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need? [112.12974778019304]
  generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. In the era of AI transitioning from pure analysis to creation, it is worth noting that ChatGPT, with its most recent language model GPT-4, is just a tool out of numerous AIGC tasks. This work focuses on the technological development of various AIGC tasks based on their output type, including text, images, videos, 3D content, etc.
  arXiv  Detail & Related papers  (2023-03-21T10:09:47Z)
• DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis [84.80347062834517]
  We introduce DiaASQ, aiming to detect the quadruple of target-aspect-opinion-sentiment in a dialogue. We manually construct a large-scale high-quality DiaASQ dataset in both Chinese and English languages. We develop a neural model to benchmark the task, which advances in effectively performing end-to-end quadruple prediction.
  arXiv  Detail & Related papers  (2022-11-10T17:18:20Z)
• The AI Index 2022 Annual Report [22.73860407733525]
  The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Its mission is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public. The report aims to be the world's most credible and authoritative source for data and insights about AI.
  arXiv  Detail & Related papers  (2022-05-02T20:59:33Z)
• Automatic Evaluation and Moderation of Open-domain Dialogue Systems [59.305712262126264]
  A long standing challenge that bothers the researchers is the lack of effective automatic evaluation metrics. This paper describes the data, baselines and results obtained for the Track 5 at the Dialogue System Technology Challenge 10 (DSTC10)
  arXiv  Detail & Related papers  (2021-11-03T10:08:05Z)
• A User-Centred Framework for Explainable Artificial Intelligence in Human-Robot Interaction [70.11080854486953]
  We propose a user-centred framework for XAI that focuses on its social-interactive aspect. The framework aims to provide a structure for interactive XAI solutions thought for non-expert users.
  arXiv  Detail & Related papers  (2021-09-27T09:56:23Z)
• The Threat of Offensive AI to Organizations [52.011307264694665]
  This survey explores the threat of offensive AI on organizations. First, we discuss how AI changes the adversary's methods, strategies, goals, and overall attack model. Then, through a literature review, we identify 33 offensive AI capabilities which adversaries can use to enhance their attacks.
  arXiv  Detail & Related papers  (2021-06-30T01:03:28Z)

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.