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Partisan news media, which often publish extremely biased, one-sided or even false news, are gaining popularity world-wide and represent a major societal issue. Due to a growing number of such media, a need for automatic detection approaches is of high demand. Automatic detection relies on various indicators (e.g. content characteristics) to identify new partisan media candidates and to predict their level of partisanship. The aim of the research is to investigate to a deeper extent whether it would be appropriate to rely on the hyperlinks as possible indicators for better automatic partisan news media detection.

The authors utilized hyperlink network analysis to study the hyperlinks of partisan and mainstream media. The dataset involved the hyperlinks of 18 mainstream media and 15 partisan media in Slovakia and Czech Republic. More than 171 million domain pairs of inbound and outbound hyperlinks of selected online news media were collected with Ahrefs tool, analyzed and visualized with Gephi software. Additionally, 300 articles covering COVID-19 from both types of media were selected for content analysis of hyperlinks to verify the reliability of quantitative analysis and to provide more detailed analysis.

The authors conclude that hyperlinks are reliable indicators of media affinity and linking patterns could contribute to partisan news detection. The authors found out that especially the incoming links with dofollow attribute to news websites are reliable indicators for assessing the type of media, as partisan media rarely receive links with dofollow attribute from mainstream media. The outgoing links are not such reliable indicators as both mainstream and partisan media link to mainstream sources similarly.

In contrast to the extensive amount of research aiming at fake news detection within a piece of text or multimedia content (e.g. news articles, social media posts), the authors shift to characterization of the whole news media. In addition, the authors did a geographical shift from more researched US-based media to so far under-researched European context, particularly Central Europe. The results and conclusions can serve as a guide how to derive new features for an automatic detection of possibly partisan news media by means of artificial intelligence (AI).

The peer review history for this article is available at the following link: https://publons.com/publon/10.1108/OIR-10-2020-0441.

This study aims to map the information landscape as it unfolds to users when they search for health topics on general search engines. Website sponsorship, platform type and linking patterns were analysed in order to advance the understanding of the provision of health information online.

The landscape was sampled by ten very different search queries and crawled with VOSON software. Drawing on Roger's framework of information politics on the web, the landscape is described on two levels. The front-end is examined qualitatively by assessing website sponsorship and platform type. On the back-end, linking patterns are analysed using hyperlink network analysis.

A vast majority of the websites have commercial and organisational sponsorship. The analysis of the platform type shows that health information is provided mainly on static homepages, informational portals and general news sites. A comparison of ten different health domains revealed substantial differences in their landscapes, related to domain-specific characteristics.

The size and properties of the web crawl were shaped by using third party software, and the generalisability of the results is limited by the selected search queries. Further research exploring how specific characteristics of different health domains shape provision of information online is suggested.

The demonstrated method can be used by organisations to discern the characteristics of the online information landscape in which they operate and to inform their business strategies.

The study examines health information landscapes on a large scale and makes an original contribution by comparing them across ten different health domains.

The aim of this study is to propose an efficient rule extraction and integration approach for identifying phishing websites. The proposed approach can elucidate patterns of phishing websites and identify them accurately.

Hyperlink indicators along with URL-based features are used to build the identification model. In the proposed approach, very simple rules are first extracted based on individual features to provide meaningful and easy-to-understand rules. Then, the F-measure score is used to select high-quality rules for identifying phishing websites. To construct a reliable and promising phishing website identification model, the selected rules are integrated using a simple neural network model.

Experiments conducted using self-collected and benchmark data sets show that the proposed approach outperforms 16 commonly used classifiers (including seven non–rule-based and four rule-based classifiers as well as five deep learning models) in terms of interpretability and identification performance.

Investigating patterns of phishing websites based on hyperlink indicators using the efficient rule-based approach is innovative. It is not only helpful for identifying phishing websites, but also beneficial for extracting simple and understandable rules.

Based on theories related to coopetition, the purpose of this paper is to examine the patterns of business-to-business digital referrals inscribed in businesses’ digital content.

A complete industry-wise digital data set is formed by extracting digital referrals in all the content pages. The authors outline how digital referrals are strategically used among peer businesses in the peer-to-peer digital network and in the augmented digital network, taking into consideration geographical framing and physical distance.

The authors reveal how geographical framing and physical distance influence peer-to-peer referral patterns in the digital space. Quite counter-intuitively, businesses are more likely to give digital referrals for peers residing in the same region, as well as for peers located in closer proximity. Further, results from the augmented digital network show that peer businesses in closer proximity exhibit greater strategic similarity in their digital referring strategy.

The findings extend the understanding of business-to-business coopetition to the digital space and suggest that geographical framing and physical distance can induce reciprocated relationships between peers by offering each other digital referrals.

The findings shed light on the formation of a business-to-business digital coopetition strategy using digital referral marketing.

This study highlights the impact of digital referrals in business-to-business relationship management, especially in the digital coopetition context.

South Korea imposes more stringent restrictions on political speeches during elections than many other democratic countries. The purpose of this paper is to examine the long‐standing conflict between citizens and institutions in the Korean electoral environment and the effects of the internet on this conflict.

The paper provides a case study of the 2007 presidential election in Korea. During the campaign period, two video clips (one on YouTube and the other on Daum, a major domestic web portal) emerged and implicated the then‐leading candidate in a financial scandal. The paper investigates how these video clips were shared and discussed among Korean voters, even though the country's election laws restricted the sharing of such information in cyberspace. The paper employs a combination of network analysis techniques, including hyperlink analysis, interaction network analysis, and semantic network analysis.

YouTube served as a medium for Korean voters to circumvent local electoral regulations, thus implying the neologism “cyber‐exile”. However, unlike Daum, YouTube failed to facilitate discussions on the posted video clip. The discussion through its comment feature was often derailed by irrelevant comments from seemingly uninterested parties. The address of the video clip was shared through personal blogs and online bulletin boards in Korean cyberspace, but these efforts led only to a fragmented sphere.

Any comparison between YouTube and Daum should be made with caution because of inherent differences between the two platforms.

The results have important practical implications for those interested in designing e‐deliberation environments. For example, they should have a clearer understanding of the composition of users and the undesirable consequences of a fragmented public sphere.

This paper highlights how pre‐internet institutions shape its members’ political activity on the internet. In addition, the results clearly demonstrate that an innovative effort to circumvent barriers on the part of internet users is not enough to harness the potential of online discussions for a measured and sustained discourse on the issue at hand.

Using Travelpod.com, this paper aims to provide a methodology to locate central groups of travelers and to describe pattern characteristics of central travelers.

The paper uses snowball sampling to locate travelers and analyze their hyperlink interconnections to identify central travelers' groups. Analysis of the adjacency matrix of the social network of travelers using multidimensional scaling and hierarchical cluster analysis to identify core travelers' groups follows.

In total, 7 percent of travelers are considered central travelers. They form core groups containing the most active and information providing travelers. Group membership is correlated with common travelers' characteristics.

The research is limited to a specific network of travelers, to a specific time interval, and to a specific sampling method. Repetition of the study in other travelers' networks in several time instances using a full list of member travelers would help to generalize the findings. Also, graph theoretical approaches other than the statistical analysis used could reveal more properties.

Travelers in core groups are more likely to be reached by others who navigate through a series of incoming links that lead to them and it is probable that these travelers have the potential to address many visitors and therefore to have a significant impact on the provision of information.

The originality of the paper lies in the use of multivariate statistics on the network adjacency matrix to locate core travelers groups and on finding groups of the most influential travelers.

Entrepreneurial ecosystems provide the context for start-ups to access resources. The authors investigate the reliance of start-ups on their entrepreneurial ecosystem and the driving factors behind the proportion of local actors (belonging to their entrepreneurial ecosystem) within their overall set of relationships (their business ecosystem). Recognizing the limited relational capacity of firms, the authors focus on three differentiating firm characteristics: size, age and innovation of firms.

The authors developed a sample of 163 start-ups located in the entrepreneurial ecosystem of Toulouse, France. The authors investigated the characteristics of their relationship sets using regression analysis.

The results confirm that age is inversely related to the proportion of a start-up's relationships located in its entrepreneurial ecosystem. More surprisingly, for older start-ups, the authors also highlight the presence of a moderating effect of the start-up's size on the relationship between its degree of innovation and the proportion of its relationships in its entrepreneurial ecosystem: Larger and more innovative start-ups appear to rely more on their local entrepreneurial ecosystem.

This research increases the understanding of the characteristics driving the interactions of start-ups with their entrepreneurial ecosystems by adopting a relational capacity approach. The authors introduce digital methods as an innovative approach for uncovering firms' ecosystems. Finally, from a practical point of view, the research should provide public authorities seeking to promote the link between local resources and the development of innovative start-ups in their regions with interesting insights.