Landscape of Generative AI in Global News: Topics, Sentiments, and
Spatiotemporal Analysis
- URL: http://arxiv.org/abs/2401.08899v1
- Date: Wed, 17 Jan 2024 00:53:31 GMT
- Title: Landscape of Generative AI in Global News: Topics, Sentiments, and
Spatiotemporal Analysis
- Authors: Lu Xian, Lingyao Li, Yiwei Xu, Ben Zefeng Zhang, Libby Hemphill
- Abstract summary: Generative AI has exhibited considerable potential to transform various industries and public life.
The role of news media coverage of generative AI is pivotal in shaping public perceptions and judgments about this significant technological innovation.
This paper provides in-depth analysis and rich insights into the temporal and spatial distribution of topics, sentiment, and substantive themes within global news coverage focusing on generative AI.
- Score: 1.5249435285717095
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Generative AI has exhibited considerable potential to transform various
industries and public life. The role of news media coverage of generative AI is
pivotal in shaping public perceptions and judgments about this significant
technological innovation. This paper provides in-depth analysis and rich
insights into the temporal and spatial distribution of topics, sentiment, and
substantive themes within global news coverage focusing on the latest emerging
technology --generative AI. We collected a comprehensive dataset of news
articles (January 2018 to November 2023, N = 24,827). For topic modeling, we
employed the BERTopic technique and combined it with qualitative coding to
identify semantic themes. Subsequently, sentiment analysis was conducted using
the RoBERTa-base model. Analysis of temporal patterns in the data reveals
notable variability in coverage across key topics--business, corporate
technological development, regulation and security, and education--with spikes
in articles coinciding with major AI developments and policy discussions.
Sentiment analysis shows a predominantly neutral to positive media stance, with
the business-related articles exhibiting more positive sentiment, while
regulation and security articles receive a reserved, neutral to negative
sentiment. Our study offers a valuable framework to investigate global news
discourse and evaluate news attitudes and themes related to emerging
technologies.
Related papers
- Guiding the Way: A Comprehensive Examination of AI Guidelines in Global Media [0.0]
This study analyzes 37 AI guidelines for media purposes in 17 countries.
Our analysis reveals key thematic areas, such as transparency, accountability, fairness, privacy, and the preservation of journalistic values.
Results highlight shared principles and best practices that emerge from these guidelines.
arXiv Detail & Related papers (2024-05-07T22:47:56Z) - The Social Impact of Generative AI: An Analysis on ChatGPT [0.7401425472034117]
The rapid development of Generative AI models has sparked heated discussions regarding their benefits, limitations, and associated risks.
Generative models hold immense promise across multiple domains, such as healthcare, finance, and education, to cite a few.
This paper adopts a methodology to delve into the societal implications of Generative AI tools, focusing primarily on the case of ChatGPT.
arXiv Detail & Related papers (2024-03-07T17:14:22Z) - Position Paper: Agent AI Towards a Holistic Intelligence [53.35971598180146]
We emphasize developing Agent AI -- an embodied system that integrates large foundation models into agent actions.
In this paper, we propose a novel large action model to achieve embodied intelligent behavior, the Agent Foundation Model.
arXiv Detail & Related papers (2024-02-28T16:09:56Z) - Tackling Cyberattacks through AI-based Reactive Systems: A Holistic Review and Future Vision [0.10923877073891446]
This paper presents a comprehensive survey of recent advancements in AI-driven threat response systems.
The most recent survey covering the AI reaction domain was conducted in 2017.
A total of seven research challenges have been identified, pointing out potential gaps and suggesting possible areas of development.
arXiv Detail & Related papers (2023-12-11T09:17:01Z) - The Rise of Creative Machines: Exploring the Impact of Generative AI [0.04464488398592258]
This study looks at how generative artificial intelligence (AI) can revolutionize marketing, product development, and research.
In addition to addressing mitigating techniques for issues like prejudice and disinformation, the debate emphasizes the significance of responsible development through continual stakeholder communication and ethical principles.
arXiv Detail & Related papers (2023-11-22T09:27:08Z) - GPT-4V(ision) as A Social Media Analysis Engine [77.23394183063238]
This paper explores GPT-4V's capabilities for social multimedia analysis.
We select five representative tasks, including sentiment analysis, hate speech detection, fake news identification, demographic inference, and political ideology detection.
GPT-4V demonstrates remarkable efficacy in these tasks, showcasing strengths such as joint understanding of image-text pairs, contextual and cultural awareness, and extensive commonsense knowledge.
arXiv Detail & Related papers (2023-11-13T18:36:50Z) - Anticipating Impacts: Using Large-Scale Scenario Writing to Explore
Diverse Implications of Generative AI in the News Environment [3.660182910533372]
We aim to broaden the perspective and capture the expectations of three stakeholder groups about the potential negative impacts of generative AI.
We apply scenario writing and use participatory foresight to delve into cognitively diverse imaginations of the future.
We conclude by discussing the usefulness of scenario-writing and participatory foresight as a toolbox for generative AI impact assessment.
arXiv Detail & Related papers (2023-10-10T06:59:27Z) - EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble
Architecture [63.85863519876587]
Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks.
We propose a new ensemble architecture, EDSA-Ensemble, that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media.
arXiv Detail & Related papers (2023-01-30T11:56:08Z) - Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on
Neuro-Symbolic Computing [66.91310801654548]
Neural-symbolic computing (NeSy) has been an active research area of Artificial Intelligence (AI) for many years.
NeSy shows promise of reconciling the advantages of reasoning and interpretability of symbolic representation and robust learning in neural networks.
arXiv Detail & Related papers (2022-10-28T04:38:10Z) - Characterising Research Areas in the field of AI [68.8204255655161]
We identified the main conceptual themes by performing clustering analysis on the co-occurrence network of topics.
The results highlight the growing academic interest in research themes like deep learning, machine learning, and internet of things.
arXiv Detail & Related papers (2022-05-26T16:30:30Z) - Survey on Visual Sentiment Analysis [87.20223213370004]
This paper reviews pertinent publications and tries to present an exhaustive overview of the field of Visual Sentiment Analysis.
The paper also describes principles of design of general Visual Sentiment Analysis systems from three main points of view.
A formalization of the problem is discussed, considering different levels of granularity, as well as the components that can affect the sentiment toward an image in different ways.
arXiv Detail & Related papers (2020-04-24T10:15:22Z)
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.