Media Hype Research Articles

Artificial intelligence and innovation management: Charting the evolving landscape

The excitement surrounding Artificial Intelligence (AI) is palpable. It is rapidly gaining prevalence in academia, business, and personal use. In particular, the emergence of generative AI, exemplified by large language models such as ChatGPT, has been marked by substantial media attention, discourse, and hype. Like most, if not all, aspects of business, innovation processes have been impacted. However, little is known about the degree of impact or the benefits that might be gained. To cut through the hype and understand the use of AI in innovation processes in businesses today, a large-scale survey amongst innovation managers in the USA was conducted, followed by interviews. The findings indicate that the use of AI in innovation processes is high and widespread, with AI being used for more than half of the surveyed firms' innovation projects. Furthermore, AI is used more in the development stage of the innovation process than in the idea or commercialization stages, which counters much of the existing discourse, which focuses on the idea stage. We uncover interesting differences by comparing the use and impact of generative AI with that of more traditional AI. Among these is a significant difference in expected benefits in making employees’ jobs more fulfilling — managers believe generative AI is more likely to confer this benefit than traditional AI. This paper offers two valuable contributions. First, it enriches the evolving dialogue at the intersection of AI and innovation management by offering much-needed empirical evidence about practical applications. Second, it provides timely managerial implications by examining relationships between the use of AI and innovation performance and understanding the benefits that AI can confer in the innovation process.

Shifting job expectations in the era of generative AI hype – perspectives of journalists and copywriters

PurposeThis interview study examines Hungarian journalists' and copywriters' expectations of generative AI’s impact on their professions and factors influencing these views during a period of hype.Design/methodology/approachWhile acknowledging the specialized knowledge of journalists and copywriters relative to the general public, the study employs the sociology of expectations framework to interpret their anticipations not as objective forecasts of the future, but rather as phenomena shaped by diverse influences. The research comprises 30 semi-structured interviews conducted in spring 2023 to explore these expectations and their contributing factors.FindingsResults reveal ChatGPT’s media coverage as pivotal, encouraging the professionals interviewed to experiment with AI, reassess their roles, and cause a shift in their job expectations. At the same time, this shift was limited. Skepticism about hyperbolic media formulations, their own experiences with ChatGPT and projecting its constraints into the future, contextual factors, and optimism bias contributed to moderating their expectations. They perceived AI as an enhancer of efficiency and quality, not as a radical disruptor. Copywriters were more open to integrating AI in their work, than journalists.Research limitations/implicationsThe results underscore the importance of further research to explore subjective experiences associated with technological change, particularly considering their complex social, psychological, and cultural influences.Originality/valueThe study uniquely contributes to the sociology of expectations by highlighting how a complex interplay of factors can shape professionals' anticipation of the impact of AI on their careers, including optimism bias and media hype.

Metaverse: the post--hype future

PurposeBeyond its initial hype, and based on original new surveying, this paper explores the impact of metaverse on business in the medium to long-term.MethodologyIBM Institute for Business Value, in collaboration with Oxford Economics, surveyed 400 C-Suite executives, (CEOs, CIO/CTOs and CMOs) in the U.S. across 25 industries on their investments in metaverse, business cases and outcomes.FindingsDespite the media hype, the majority of investment in metaverse is B2B.Although the biggest impacts of metaverse are medium to long-term, there are benefits immediately accessible in the short-term.More success is likely if organizations develop metaverse strategies with ecosystem partners.Research implicationsMetaverse was extremely fashionable, now far less so. Both extremes are inappropriate. Metaverse, especially as a B2B strategy, has an important role to play in an organizations' strategy.Practical implicationsMany businesses are making investments in metaverse. They should continue.Social implicationsMetaverse impacts extends beyond B2C applications into the B2B workplace.Originality and valueThis work is completely original, based on new data and analysis that has not been published elsewhere.

From hype to insight: Exploring ChatGPT's early footprint in education via altmetrics and bibliometrics

AbstractBackgroundThe emergence of ChatGPT in the education literature represents a transformative phase in educational technology research, marked by a surge in publications driven by initial research interest in new topics and media hype. While these publications highlight ChatGPT's potential in education, concerns arise regarding their quality, methodology, and uniqueness.ObjectiveOur study employs unconventional methods by combining altmetrics and bibliometrics to explore ChatGPT in education comprehensively.MethodsTwo scholarly databases, Web of Science and Altmetric, were adopted to retrieve publications with citations and those mentioned on social media, respectively. We used a search query, “ChatGPT,” and set the publication date between November 30th, 2022, and August 31st, 2023. Both datasets were within the education‐related domains. Through a filtering process, we identified three publication categories: 49 papers with both altmetrics and citations, 60 with altmetrics only, and 66 with citations only. Descriptive statistical analysis was conducted on all three lists of papers, further dividing the entire collection into three distinct periods. All the selected papers underwent detailed coding regarding open access, paper types, subject domains, and learner levels. Furthermore, we analysed the keywords occurring and visualized clusters of the co‐occurring keywords.Results and ConclusionsAn intriguing finding is the significant correlation between media/social media mentions and academic citations in ChatGPT in education papers, underscoring the transformative potential of ChatGPT and the urgency of its incorporation into practice. Our keyword analysis also reveals distinctions between the themes of the papers that received both mentions and citations and those that received only citations but no mentions. Additionally, we noticed a limitation that authors' choice of keywords might be influenced by individual subjective judgements, potentially skewing results in thematic analysis based solely on author‐assigned keywords such as keyword co‐occurrence analysis. Henceforth, we advocate for developing a standardized keyword taxonomy in the educational technology field and integrating Large Language Models to enhance keyword analysis in altmetric and bibliometric tools. This study reveals that ChatGPT in education literature is evolving from rapid publication to rigorous research.

Panic News and media Hype Effects on Stock Market Returns and Volatility amid Infectious Diseases Turmoil

This study investigates the effect of fake news, panic news, and media hype on stock market returns amid COVID-19 in Pakistan. It also scrutinizes the asymmetric effect of bad and good news on stock market volatility. For empirical analysis, data of six indicators related to news collected from Ravenpack. The data is ranged from the date of first COVID-19 case recognition dated February 26, 2020, to October 26, 2020. This time span consist on the 166 working days in which stock market remains open. The estimates of the Multivariate EGARCH model revealed that fake news and media hype is negatively associated with the stock market returns. The negative effect of media hype is greater than fake news. The aftermath of variance equation suggests that media hype, infodemic, and panic new increase the stock market volatility. The findings of the study suggests that strong co-ordination among NCOC and Information ministry may result in stabilizing the stock market return by enhancing the investors’ confidence and reducing the panic.

COVID-19 pandemic-related news and Chinese commodities futures: Time-frequency connectedness and causality-in-quantiles approaches

The COVID-19 pandemic has had a significant impact on the global economy and commodity markets, making it essential to study its effects. We aim to learn the dynamic spillovers between COVID-19 pandemic-related news and Chinese commodities futures (Energy, Petrochemical, Non-ferrous metals, Oil & Fats, and Softs) using time-frequency connectedness and causality-in-quantiles approaches. To capture the diverse impacts of different types of COVID-19 news, we utilize a range of COVID-19 news-related indices based on media news data from January 2, 2020, to October 28, 2022. Based on static connectedness data, it is evident that Petrochemical and Energy futures commodities are the primary contributors and recipients in our research samples. The short- and long-term data sets consistently demonstrate that COVID-19 uncertainty is the main recipient, and they have heterogeneous effects on the commodities. Interestingly, the Coronavirus Panic Index and Coronavirus Media Hype Index show the greatest influence on commodities. Dynamic data reveals that the level of connectedness among the markets fluctuates significantly over time, and short-term connectedness is higher than that in the long term. The non-parametric Granger causality test shows that COVID-19 uncertainty can significantly impact commodities futures in China. Specifically, the results remain robust even when utilizing various uncertainty measures and distinct quantiles.

Impact of media hype and fake news on commodity futures prices: A deep learning approach over the COVID-19 period

We investigate the reactions of eight commodity futures to media hype and fake news during COVID-19, utilising the Ravenpack news database, along with deep learning algorithms. Results identify a significant impact on commodity prices of media hype and fake news, with this reaction amplified during COVID-19. Compared to alternative deep learning algorithms, bi-directional long-short-term memory is adaptive to forecasting the returns of the commodity futures contracts with lower mean absolute error and root mean square error. Findings, confirmed by Diebold-Mariano testing, as well as alternative data partitioning, show commodity markets are susceptible to fake news and media hype.

STATUS QUO OF CHINESE CULTURAL INHERITANCE

Chinese culture has a long history and is one of the oldest ancient civilizations. In the course of thousands of years of development, the Chinese nation has created a rich and splendid Chinese culture. Chinese culture is the spiritual pillar for the long-term continuation and continuous development of the Chinese nation. The main spiritual core of Chinese culture is Confucian culture, which has been inherited for thousands of years. Confucian culture is the muscle and bone of Chinese culture. Meanwhile, Taoism, as a local religion, and Buddhism, which is integrated with society in the history of Chinese civilization for thousands of years. Chinese culture has been influenced by foreign cultures and embraces fine foreign cultures. The rapid development of national economy and the integration of global economy have accelerated the influence of foreign culture on China. Media and business hype, promote the "foreign festival" is heating up, behind which is mainly huge commercial profits; It is also inevitable that the Chinese people begin to lead a rich life and pursue a rich and colorful spiritual life. At the same time, traditional culture is regarded by a large number of young people as dross, feudal superstition, backward and unprogressive representative. Chinese culture has thrown off its shackles, been in line with The Times, actively innovated, and carried out new media communication. More and more people have spontaneously joined the camp of protecting cultural inheritance. The method of cultural inheritance also changes with The Times, but what remains unchanged is the sense of belonging to culture.

Media Hype and The True Coverage of Episodes in Human endurance – A Content analysis of a Vernacular News Channel

Media Hype and The True Coverage of Episodes in Human endurance – A Content analysis of a Vernacular News Channel

PYRO TERROR: FOREST ARSONS

ntroduction: Stereotypes and pre judice are human traits. It seems that they accompanied humanity since its beginning when people saw or meet somebody, and had to judge him as an enemy or as a friend. In this view, these traits are part of the evolution of human kind, hence, they should be important and valued. Is it? As we will show these traits may destroy the life not only of a person, but those of communities that are different in their origin, nationality, gender, skin color and age. People may be labelled as dangerous to society in accordance to their born status, and they may nd themselves at the lowest strata of their society or culture (Adams -Quackenbush et al. 2019; Barlow & Barlow, 2002; Deskins et. Al. 2017; Park & Wittenbrink, 2002; Plous, 2003). Our article addresses stereotypes and pre judice as an attitude, conscious or unconscious, among the public in relation to forest arsons in Israel. These attitudes are common among the police, and the judicial system. The personal of these systems are members of the culture, inuence by it and inuence back on it. In other words these personal are mirror of the attitudes which are common in the society they serve and inuence this society until there is a loop of attitudes between culture, society and the judicial system. Many studies found out that police ofcers, prosecutors and even judges use the notion of proling to mark certain marginal groups as more dangerous to society. This so-called proling justies arrests, prosecutes, and more severe punishment in the name of society's security. As a result, the mass media and the public accept this proling and develop stereotypes and prejudgment against these groups. In many countries these traits address against immigrants, women, young people, black skin color and other characteristics, which make them more vulnerable to media hype, being arrest more easily and punish more severely. As a result, they become more exposed to negative labels and pre judice. Our article addresses these issues in relation to arson in Israel and show how stereotypes and pre judice among the public make the media and the public to believe that and to blame Arabs in eco terrorism of forest arsons, while the data shows that only 2% of the arsons are motives by national ideology (i.e., Terror).

Unmasking the Effect of News Media on Islamic Stock Market: Are ASEAN-3 Countries Vulnerable to Covid-19 News?

This study provides a novel viewpoint by clarifying the effect of the COVID-19 news on the fluctuations of the Islamic capital market in the ASEAN Region. It aims to explore the effect of news related to the COVID-19 pandemic on the movement of the Islamic stock index in ASEAN-3 countries (Indonesia, Malaysia, Thailand). This research examined five news-related indices: panic emotion index, media hype index, sentiment index, fake news index, and contagion index. The research employed long-term daily secondary data covering one year during the COVID-19 pandemic to test the hypothesis. A total of 1086 data were analyzed using the panel regression method through EViews 9. The findings indicated that news media and the resulting sentiment have the potential to negatively affect the Islamic stock index movement through the panic and media hype index. The excitement and panic caused by the online news media negatively affected the movement of Islamic stock prices in the three ASEAN Islamic stock indexes, whereas fake news and contagion index were found to have no significant effect on the stock index movement.

Role of proliferation COVID-19 media chatter in predicting Indian stock market: Integrated framework of nonlinear feature transformation and advanced AI

The outbreak of the COVID-19 pandemic has transpired the global media to gallop with reports and news on the novel Coronavirus. The intensity of the news chatter on various aspects of the pandemic, in conjunction with the sentiment of the same, accounts for the uncertainty of investors linked to financial markets. In this research, Artificial Intelligence (AI) driven frameworks have been propounded to gauge the proliferation of COVID-19 news towards Indian stock markets through the lens of predictive modelling. Two hybrid predictive frameworks, UMAP-LSTM and ISOMAP-GBR, have been constructed to accurately forecast the daily stock prices of 10 Indian companies of different industry verticals using several systematic media chatter indices related to the COVID-19 pandemic alongside several orthodox technical indicators and macroeconomic variables. The outcome of the rigorous predictive exercise rationalizes the utility of monitoring relevant media news worldwide and in India. Additional model interpretation using Explainable AI (XAI) methodologies indicates that a high quantum of overall media hype, media coverage, fake news, etc., leads to bearish market regimes.

Prediction and interpretation of daily NFT and DeFi prices dynamics: Inspection through ensemble machine learning & XAI

Non Fungible Tokens (NFT) and Decentralized Finance (DeFi) assets have seen a growing media coverage and garnered considerable investor traction despite being classified as a niche in the digital financial sector. The lack of substantial research to demystify the dynamics of NFT and DeFi coins motivates the scrupulous analysis of the said sector. This work aims to critically delve into the evolutionary pattern of the NFTs and DeFis for performing predictive analytics of the same during the COVID-19 regime. The multivariate framework comprises the systematic inclusion of explanatory features embodying technical indicators, key macroeconomic indicators, and constructs linked to media hype and sentiment pertinent to the pandemic, nonlinear feature engineering, and ensemble machine learning. Isometric Mapping (ISOMAP) and Uniform Manifold Approximation and Projection (UMAP) techniques are conjugated with Gradient Boosting Regression (GBR) and Random Forest (RF) for enabling the predictive analysis. The predictive performance rationalizes the frameworks' capacity to accurately predict the prices of the majority of the NFT and DeFi coins during the ongoing financial distress period. Additionally, Explainable Artificial Intelligence (XAI) methodologies are used to comprehend the nature of the impact of the explanatory variables. Findings suggest that the daily movement of the NFTs and DeFi highly depends on their past historical movement.

“Collaborating” with AI: Taking a System View to Explore the Future of Work

In the wake of media hype about artificial intelligence (AI)/human collaboration, organizations are investing considerable resources into developing and using AI. In this paper, we draw on theories of technology in organizations to frame new directions for the study of what it means to work “with” AI. Drawing on prior literature, we consider how interactions between users and AI might unfold through theoretical lenses which cast technology as a tool and as a medium. Reflecting on how AI technologies diverge from technologies studied in the past, we propose a new perspective, which considers technology as a counterpart in a system of work that includes its design, implementation, and use. This perspective encourages developing a grounded understanding of how AI intersects with work, and therefore ethnography, building on thick descriptions, is an apt approach. We argue that relational ethnographic approaches can assist organization theorists in navigating the methodological challenges of taking a counterpart perspective and propose several strategies for future research.

Enhancing Cryptocurrency Price Forecasting Accuracy: A Feature Selection and Weighting Approach With Bi-Directional LSTM and Trend-Preserving Model Bias Correction

A cryptocurrency is a digitized, encrypted, and decentralized virtual currency, which is impossible to counterfeit or double-spend. It is one of the very popular investment instruments and traded in blockchain based crypto exchanges on ever growing volume. It is quite volatile due to imbalance of supply and demand, government regulations, investor sentiment and above all media hype. Cryptocurrency price forecasting is an active area of research and several approaches have been proposed recently. This study proposed a price forecasting model based on three vital characteristics (i) a feature selection and weighting approach based on Mean Decrease Impurity(MDI) features. (ii) Bi-directional LSTM and (iii) with a trend preserving model bias correction (CUSUM control charts for monitoring the model performance over time) to forecast Bitcoin and Ethereum values for long and short term spans. The data for both currencies were analyzed in three different intervals: (i) April 01, 2013 to April 01, 2016 (ii) April 01, 2013 to April 01, 2017 and (iii) April 01, 2013 to December 31, 2019. Extensive series of experiments were performed and evaluated on Root Mean Square Errors (RMSE). Comparing with the prevalent forecasting models we report a new state of the art in cryptocurrency forecasting.

Cartoons of the Baghdad Railway: A Media Hype in German, French and British Journals

Starting around the turn of the twentieth century and abruptly declining with the First World War, public discussions on the Baghdad Railway made international headlines and cartoons captured widespread interest as a medium of communication. Pictorial representations where illustrators were able to simplify and exaggerate themes attracted much attention and enabled the fears and expectations regarding the construction project to be articulated in an unfiltered way. The European public debates appearing in satirical magazines in caricature format presented here chronologically allowed the audience to follow the heated discussions in Europe on the construction of initially the Anatolian and thereafter the Baghdad Railway.

Aylan, Yaguine et Fodé, réponses artistiques à l’emballement médiatique

En confrontant les trajectoires de Aylan, Yaguine et Fodé ‒ trois enfants décédés sur les routes de l’exil, devenus malgré eux des icônes médiatiques ‒ à la manière dont des artistes réinvestissent leurs parcours, il s’agira de se demander si ces productions sont en mesure d’opposer de la pensée au scandale, et à quelles conditions. Pour autant, si le traitement journalistique peut contribuer sous certains aspects à l’hystérisation, entendue comme spectacularisation et brutalisation du débat public, il ne saurait s’y réduire. Représenter autrement la migration ne se réduit pas à une contre-représentation idéologique des personnes dites migrantes ; c’est encore moins ajouter de la déliaison à la déliaison, c’est permettre de penser les conditions possibles d’édification d’un monde véritablement commun.

Impact of COVID-19 on mental health of primary healthcare workers in Pakistan: lessons from a qualitative inquiry

ObjectivesThe existing literature regarding the mental health consequences of COVID-19 among healthcare workers revolves predominantly around specialised hospital settings, while neglecting primary healthcare workers (PHCW) who are the first point...

Identification of Decreased Butyrylcholinesterase in Sudden Infant Death Syndrome Is, at Best, a First Step Toward Preventive Screening.

The identification of a biomarker associated with increased risk of sudden infant death syndrome (SIDS), as described by Harrington et al. (1) is an exciting yet cautionary tale combining the incremental progress of scientific research and the hazards of media hype. The authors propose an association of decreased butyrylcholinesterase (BChE) activity levels in newborn screening (NBS) dried blood spots collected from infants who died of SIDS compared to surviving controls. This association was not seen in a cohort of non-SIDS deaths when compared to surviving controls. The authors theorize that decreased BChE activity is a marker for autonomic dysfunction, a vulnerability previously suspected to be implicated in the triple risk model for SIDS (2). While considerable decreases in SIDS deaths have been accomplished through NBS programs and safe sleep education, a significant number of infants still die of SIDS, and other promising diagnostic approaches (e.g., genomic analyses) are so far only pursued in the research environment (3). Harringtons study had a robust design with well-defined cases and controls. Utilizing NBS dried blood samples recognizes the need for future screening to work within existing systems for sample collection and availability, and takes advantage of preserved samples for the potential benefit of babies and families in the future. This study was made possible in part by the recognition that stored NBS blood samples can provide valuable information for future expansion of NBS panels. The rarity of most conditions targeted for NBS precludes prospective case identification. Regions that destroy samples after short retention periods are limiting opportunities for improvement and expansion of screening programs, as well as for families to obtain critical information from these samples.

Debate: Innovations in mindfulness for young people need to take more account of their unique needs if they are to live up to their potential.

While the current popularity of mindfulness suggests that it will foster various social-emotional, personal, and academic benefits, current claims for the benefits of mindfulness for children and young people is premature according to Butterfield, Roberts, Feltis, and Kocovski (2020) who argue that 'despite the media hype and the increase in peer-reviewed publications the evidence base for mindfulness programs for children is not robust' (p. 194). A recent report from a large scale mindfulness project conducted by a number of highly experienced mindfulness researchers and involving more than 28,000 young people outlines that: 'For the most part the young people did not engage with the mindfulness training' and 'our results suggested mindfulness training might work for some children and not for others, and under some conditions, but not others' (https://myriadproject.org/what-we-did/). The MYRIAD project carefully tested the effects of a brief mindfulness intervention for early teens and found it to have no impact on preventing mental health problems or promoting well-being. Researchers in this project found that since the young participants were generally not particularly engaged overall in mindfulness a more engaging accessible and effective format and teaching format and mode of delivery may have been needed. Myriad researchers included students' feedback comments: 'didn't find it useful'; found it 'boring'; had 'no choice'; 'couldn't do it; didn't do it'. More concerning is their finding of potentially harmful effects leading the researchers to state that: future research and innovations should carefully consider the unique needs and developmental stage of young people (Montero-Marin etal., 2022, p. 123). I argue in this short 'debate' piece that there is a pressing need for more nuanced, broad ranging and creative qualitative research that can help us understand young people's rich subjective experience of mindfulness, why they might not engage in mindfulness and how to better tailor it for their individual needs and contexts.