scholarly journals Recommending News in Traditional Media Companies

AI Magazine ◽  
2022 ◽  
Vol 42 (3) ◽  
pp. 55-69
Author(s):  
Jon Gulla ◽  
Rolf Svendsen ◽  
Lemei Zhang ◽  
Agnes Stenbom ◽  
Jørgen Frøland

The adoption of recommender systems in online news personalization has made it possible to tailor the news stream to the individual interests of each reader. Previous research on commercial recommender systems has emphasized their use in large-scale media houses and technology companies, and real-world experiments indicate substantial improvements of click rates and user satisfaction. It is less understood how smaller media houses are coping with this new technology, how the technology affects their business models, their editorial processes, and their news production in general. Here we report on the experiences from numerous Scandinavian media houses that have experimented with various recommender strategies and streamlined their news production to provide personalized news experiences. In addition to influencing the content and style of news stories and the working environment of journalists, the news recommender systems have been part of a profound digital transformation of the whole media industry. Interestingly, many media houses have found it undesirable to automate the entire recommendation process and look for approaches that combine automatic recommendations with editorial choices.

Author(s):  
Martina Schneller

The project focuses on the employability of construction site managers since they belong to a much imperiled occupational group. Next to the impairment of health of the individual, the missing work time leads to a huge impact on the economy. Reducing the average missing work time about half a day would increase the annual production about 1.87 billion Euro. On this background the protection of employability and the avoidance of missing work time has to be the goal. The analysis of the current state was performed by different methods, i.e., online surveys, interviewing experts and recording processes on construction sites. The results of the analysis showed that construction managers are happy about their profession and that they like their job. But the results also showed that construction managers wish for a better balance between leisure and working time. A Construction Site Manager’s current working environment is molded by many challenges including: computerization, speedy development of new technology, acceleration, juridification and economization. Based on the survey the Pentagon of construction management was developed with the focus on improvement. Improvement can be in the form of practical aids, tools-such as the qualification matrix or the application for interface analysis and process optimization. Also a new concepts like the assistance of construction management. For which a modular qualification system was settled, which can be used for dual studies, as well as in a form of postgraduate education.


Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5666
Author(s):  
Cach N. Dang ◽  
María N. Moreno-García ◽  
Fernando De la Prieta

Recommender systems have been applied in a wide range of domains such as e-commerce, media, banking, and utilities. This kind of system provides personalized suggestions based on large amounts of data to increase user satisfaction. These suggestions help client select products, while organizations can increase the consumption of a product. In the case of social data, sentiment analysis can help gain better understanding of a user’s attitudes, opinions and emotions, which is beneficial to integrate in recommender systems for achieving higher recommendation reliability. On the one hand, this information can be used to complement explicit ratings given to products by users. On the other hand, sentiment analysis of items that can be derived from online news services, blogs, social media or even from the recommender systems themselves is seen as capable of providing better recommendations to users. In this study, we present and evaluate a recommendation approach that integrates sentiment analysis into collaborative filtering methods. The recommender system proposal is based on an adaptive architecture, which includes improved techniques for feature extraction and deep learning models based on sentiment analysis. The results of the empirical study performed with two popular datasets show that sentiment–based deep learning models and collaborative filtering methods can significantly improve the recommender system’s performance.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Demetris Vrontis ◽  
Gianpaolo Basile ◽  
Mario Tani ◽  
Alkis Thrassou

Purpose This paper aims to identify and elucidate the culinary territorial (regional) characteristics that may support the development of stakeholder relations with and perceptions of a territorial system. It further focuses on these support interactions between destination managers and stakeholders and how online technology can transform them into a word-of-mouth source. Design/methodology/approach The authors present a theoretical framework, stemming from a case study of a tour operator and its technological (social media, etc.) dynamics on the relational aspects between destination management and stakeholders. Through a combination of qualitative tools and secondary data analysis, this paper analyzes the interrelationships of authenticity and place-as-brand concept, considered as the set of human characteristics associated with a brand in a “living like” travel experience. Findings Culinary tourism is seen as a relevant and significant factor in facilitating interaction between the destination community and its stakeholders, and a meaningful element, which when technologically communicated and enhanced, strengthens both the perception and the brand image of a destination. Practical implications Such new technology-enhanced insights into tourists’ experience could be exploited to plan and implement destination management and development strategies in a way that would be expected, accepted and welcomed by stakeholders, including tourists themselves. In this context, this paper presents and prescribes the role of culinary characteristics and stakeholder relationship management to develop new culinary business models and different destination community approaches toward practical implementation at both the individual (business) and the collective (authorities) levels. Originality/value The proposed framework fills the gap in the role of culinary tourism resources particularly in those areas where food has no viable certification even if it essentially constitutes a manifestation of traditions.


2019 ◽  
Author(s):  
Felicia Loecherbach ◽  
Damian Trilling

Today’s online news environment is increasingly characterized by personalized news selections, relying on algorithmic solutions for extracting relevant articles and composing an individual’s news diet. Yet, the impact of such recommendation algorithms on how we consume and perceive news is still understudied. We therefore developed one of the first software solutions to conduct studies on effects of news recommender systems in a realistic setting. The web app of our framework (called 3bij3) displays real-time news articles selected by different mechanisms. 3bij3 can be used to conduct large-scale field experiments, in which participants’ use of the site can be tracked over extended periods of time. Compared to previous work, 3bij3 gives researchers control over the recommendation system under study and creates a realistic environment for the participants. It integrates web scraping, different methods to compare and classify news articles, different recommender systems, a web interface for participants, gamification elements, and a user survey to enrich the behavioral measures obtained.


Author(s):  
Cach Nhan Dang ◽  
María N. Moreno ◽  
Fernando De la Prieta

Recommender systems have been applied in a wide range of domains such as e-commerce, media, banking, and utilities. This kind of system provides personalized suggestions based on large amounts of data in order to increase user satisfaction. These suggestions help client select products, while organizations can increase the consumption of a product. In the case of social data, sentiment analysis can help gain better understanding of a user’s attitudes, opinions and emotions, which is beneficial to integrate in recommender systems for achieving higher recommendation reliability. On the one hand, this information can be used to complement explicit ratings given to products by users. On the other hand, sentiment analysis of items that can be derived from online news services, blogs, social media or even from the recommender systems themselves is seen as capable of providing better recommendations to users. In this study, we present and evaluate a recommendation approach that integrates sentiment analysis into collaborative filtering methods. The recommender system proposal is based on an adaptive architecture, which includes improved techniques for feature extraction and deep learning models based on sentiment analysis. The results of the empirical study performed with two popular datasets show that sentiment–based deep learning models and collaborative filtering methods can significantly improve the recommender system’s performance.


2020 ◽  
Vol 2 (1) ◽  
pp. 53-79
Author(s):  
Felicia Loecherbach ◽  
Damian Trilling

Abstract Today’s online news environment is increasingly characterized by personalized news selections, relying on algorithmic solutions for extracting relevant articles and composing an individual’s news diet. Yet, the impact of such recommendation algorithms on how we consume and perceive news is still understudied. We therefore developed one of the first software solutions to conduct studies on effects of news recommender systems in a realistic setting. The web app of our framework (called 3bij3) displays real-time news articles selected by different mechanisms. 3bij3 can be used to conduct large-scale field experiments, in which participants’ use of the site can be tracked over extended periods of time. Compared to previous work, 3bij3 gives researchers control over the recommendation system under study and creates a realistic environment for the participants. It integrates web scraping, different methods to compare and classify news articles, different recommender systems, a web interface for participants, gamification elements, and a user survey to enrich the behavioural measures obtained.


Author(s):  
Sheri Crofts ◽  
Mark Fox ◽  
Andrew Retsema ◽  
Bob Williams

Podcasting has become popular as it allows listeners to time–shift content, i.e., to listen — when it suits them — to radio–like programming on portable MP3 and related devices. Dissatisfaction with traditional radio — which has too much advertising and is perceived to have generic programming — is fueling interest in programming that better meets the individual needs and interests of consumers. Podcasting represents a shift from mass broadcasting to on–demand personalized media. We look at the development of podcasting technology, the social context within which this development has occurred, and outline the legal constraints that podcasters face. Then we examine some business models for podcasting.


2019 ◽  
Vol 19 (2) ◽  
pp. 143-167
Author(s):  
Rob Allen

This article is based on a qualitative interpretivist methodology that helps to analyse, interpret, and explain the meanings that executives and consultants (as social actors), construct regarding so called transformational and digital change in the corporate setting. It explores change interventions through a psychodynamic perspective that recognises many of the forces operating in an organisation may be “under the surface” and may need to be made explicit if collective progress is to be made. The author has attempted to produce research that is relevant to both practitioners and scholars by following some suggestions of Toffel (2016) to bridge the potential gap between perceptions and workplace realities, including conducting site visits, practitioner interviews, and working as a practitioner. The study is exploratory in nature and was primarily concerned with discovering what management practices (if any) are used by executives and consultants in the operationalisation and implementation of transformational and digital change and what (if any) were the implications. It hopefully provides a stimulus for further research. Qualitative interviews and site visits were conducted with executives, consultants, and workers in ten large UK companies who had all taken the decision to instigate multi-million-pound “transformational change” and “digital transformation”. The companies operate across a range of sectors including manufacturing, retail, financial services, food and beverage, and facilities management. This study finds that executives and consultants search for tools and techniques to deliver effective change capability, change leadership, and project management of change. These imply order, rationality, stability, and manageability in change that often takes place amidst absurdity, irrationality, uncertainty, and disorder. Digital transformation is underpinned by new technology, driving new business models, and new “agile” and “iterative” processes, and “dare to fail” ways of working, but it was a century-old doctrine that provided the framework for change. Executives and consultants explicitly and implicitly advocated and enacted the primary functions of management as outlined by Fayol (1916); they were obsessed with accountability and control. Despite the rhetoric of agile and iterative approaches, they were wedded to top–down mechanistic management. The espoused visions, values, principles, and behaviours, were often counterbalanced by the shadow organisation, the covert processes, coalitions, secret alliances, and counter-values. Narcissism and Machiavellian behaviour was rife. In conclusion, this article calls for a move away from mechanistic management to enlightened management, a concept based on the work of Nonaka (2008) that values individuals and interactions over processes and tools. This may go some way to ameliorate the impacts of change at the individual level and bridge the chasm between espoused culture and the living hell of organisational reality.


Author(s):  
Ruth Yeoman ◽  
Catherine Bailey ◽  
Adrian Madden ◽  
Marc Thompson

With organizations under pressure from new business models, technological change, and globalization, the prospects for meaningful work appear uncertain. Despite this, scholarly and practitioner interest in meaningful work continues to grow. This handbook examines the conceptualization, practices, and effects of meaningful work by reflecting diverse perspectives on meaningful work from philosophy, political theory, psychology, sociology, and organization studies. In philosophy, moral considerations related to meaningful work range across human flourishing, autonomy, dignity, alienation, freedom, and organizational ethics. Meanwhile, empirical studies are expanding beyond a positive psychology focus on the individual experience, to ethnographic and constructivist approaches which attend to organizational and institutional factors. Furthermore, scholars are now considering multilevel features such as leadership, voluntary work, families, and corporate social responsibility, as well as political economy and large-scale entities such as cities, national cultures, and broader meaning-systems.


Author(s):  
Yulia P. Melentyeva

In recent years as public in general and specialist have been showing big interest to the matters of reading. According to discussion and launch of the “Support and Development of Reading National Program”, many Russian libraries are organizing the large-scale events like marathons, lecture cycles, bibliographic trainings etc. which should draw attention of different social groups to reading. The individual forms of attraction to reading are used much rare. To author’s mind the main reason of such an issue has to be the lack of information about forms and methods of attraction to reading.


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