Hyperlink Network Research Articles

Location factors and ecosystem embedding of sustainability-engaged blockchain companies in the US. A web-based analysis

While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy demand. In our study, we present a novel approach to identifying sustainability-focused blockchain companies and relate their level of engagement to location factors and entrepreneurial ecosystem embeddedness. For this, we use a large-scale web scraping approach to analyze the textual content and hyperlink networks of all US companies from their websites. Our results show that blockchain remains a niche technology, with its use communicated by about 0.6% of US companies. However, the proportion of blockchain companies that are committed to sustainability is significantly higher than in the overall firm population. Additionally, we find that such sustainability-engaged blockchain companies have, at least quantitatively, a more intensive embedding in entrepreneurial ecosystems, while infrastructural and socio-economic location factors hardly play a role.

Dichotomy Graph Sketch: Summarizing Graph Streams with High Accuracy Based on Deep Learning

In many applications, data streams are indispensable to describe the relationships between nodes in networks, such as social networks, computer networks, and hyperlink networks. Fundamentally, a graph stream is a dynamic representation of a graph, which is usually composed of a sequence of edges, where each edge is represented by two endpoints and a weight. As a result of its large volume and highly dynamic nature, several graph sketches were proposed for the purposes of summarizing large-scale graph streams and enabling fast query processing. By using a compact data structure with hash functions, the graph sketches sequentially store the edges. Nevertheless, the existing graph sketches suffer from low performance on graph query tasks as a result of unpredictable collisions between heavy edges and light edges. To store heavy edges and light edges, this paper introduces a novel learning-based Dichotomy Graph Sketch (DGS) mechanism that uses two separate graph sketches, a heavy sketch and a light sketch. During a graph stream session, DGS obtains heavy edges and light edges, and uses these edges as training samples for a deep neural network (DNN) based binary classifier. The DNN-based classifier is then used to determine whether the upcoming edges are heavy or not. We will store the edges that are classified as heavy edges in the heavy sketch, and those that are classified as light edges in the light sketch. By combining the learnable classifier and Dichotomy Graph Sketches, the proposed mechanism resolves the hashing collision problem in conventional graph sketches and significantly improves graph query accuracy. The DGS algorithm outperforms the state-of-the-art graph sketches in a variety of graph query tasks based on extensive experiments that were conducted on four real-world graph stream datasets.

Epidemic effects in the diffusion of emerging digital technologies: evidence from artificial intelligence adoption

The properties of emerging, digital, general-purpose technologies make it hard to observe their adoption by firms and identify the salient determinants of adoption. However, these aspects are critical since the patterns related to early-stage diffusion establish path-dependencies which have implications for the distribution of the technological opportunities and socio-economic returns linked to these technologies. We focus on the case of artificial intelligence (AI) and train a transformer language model to identify firm-level AI adoption using textual data from over 1.1 million websites and constructing a hyperlink network that includes >380,000 firms in Germany, Austria, and Switzerland. We use these data to expand and test epidemic models of inter-firm technology diffusion by integrating the concepts of social capital and network embeddedness. We find that AI adoption is related to three epidemic effect mechanisms: 1) Indirect co-location in industrial and regional hot-spots associated to production of AI knowledge; 2) Direct exposure to sources transmitting deep AI knowledge; 3) Relational embeddedness in the AI knowledge network. The pattern of adoption identified is highly clustered and features a rather closed system of AI adopters which is likely to hinder its broader diffusion. This has implications for policy which should facilitate diffusion beyond localized clusters of expertise. Our findings also point to the need to employ a systemic perspective to investigate the relation between AI adoption and firm performance to identify whether appropriation of the benefits of AI depends on network position and social capital.

Online networking behaviour of tourism stakeholders in a multi-destination region: A hyperlink network analysis

Inter-organisational networking, essential for enhancing tourist destinations' performance, is often underutilised, resulting in low-density networks. To develop precise strategies for managing connectivity, it is crucial to examine stakeholders' networking behaviours – how they connect to a destination network and contribute to its structural formations within and beyond their sectors and geographic locations. This study looks at online networking forms that are qualitatively different from interpersonal contacts among organisational members. Specifically, it focuses on hyperlink networking, given its significance for the visibility of organisations and the overall destination and the credibility of tourism websites. Using social network analysis, this research identifies diverse online networking behaviours related to involvement in networking activities, link-placing and link-receiving, connections with similar and dissimilar actors, and community formation of tourism stakeholders across different sectors within a multi-destination region. The network is characterised by assembling behaviour, where many actors are connected to the network by other organisations rather than by their own linking activity. The study confirms organisations’ low involvement in networking and significant imbalances in their activities. It highlights how imbalances arise in the conjuncture of various sectors, each having a distinct role in uneven link allocation. Destination management organisations are key connectors and mediators but struggle to establish high-density within-sector connections. Public domain-related sectors are generally more active in networking than private ones. Intersectoral connections, rather than within-sector connections, are the major source of links for sectors. Stakeholders tend to connect more with actors from the same geographic area.

Policy advocacy, network formation and network governance

This article examines the mechanisms underlying the formation of U.S. national clean energy policy network. Informed by the Institutional Collective Action (ICA) framework, this article develops and tests hypotheses regarding cooperation versus coordination hypotheses regarding the reasons underlying clean energy policy actors’ networking activities. Using a webcrawler data collection strategy and measuring policy network with hyperlink network, a data set of network relationships among the clean energy policy actors is collected. Exponential Random Graph Models (ERGMs) are applied to test the proposed hypotheses, and results show strong empirical evidence supporting cooperation hypotheses, with partial support for coordination hypotheses.

the diaspora: China's united front work and the hyperlink networks of diasporic Chinese websites in cyberspace

ABSTRACT In recent years concerns have emerged regarding the loyalty of ethnic Chinese residing outside of China and whether they are agents of foreign influence. China has also recently declared its ambition to be an ‘Internet superpower’ and use the internet for political goals. This article will therefore explore the role of the internet in China's diaspora engagement efforts. By adopting an Information Technology (IT)-informed approach, this article seeks to provide insights to the following question(s): Does China engage in diaspora engagement on the internet, to what extent, and what are the implications of such? An in-depth look at a representative sample of Chinese-language websites outside of China reveals ‘dual-track messaging’ approaches where non-political (i.e. business) news exists alongside overtly political messages. This strongly suggests that the Communist Party of China's (CPC) United Front work to co-opt the diaspora is also taking place via cyberspace, in addition to traditional media sources.

Using the Web to Predict Regional Trade Flows: Data Extraction, Modeling, and Validation

Despite the importance of interregional trade for building effective regional economic policies, there are very few hard data to illustrate such interdependencies. We propose here a novel research framework to predict interregional trade flows by utilizing freely available Web data and machine learning algorithms. Specifically, we extract hyperlinks between archived Websites in the United Kingdom and we aggregate these data to create an interregional network of hyperlinks between geolocated and commercial Web pages over time. We also use existing interregional trade data to train our models using random forests and then make out-of-sample predictions of interregional trade flows using a rolling-forecasting framework. Our models illustrate great predictive capability with R 2 greater than 0.9. We are also able to disaggregate our predictions in terms of industrial sectors, but also at a subregional level, for which trade data are not available. In total, our models provide a proof of concept that the digital traces left behind by physical trade can help us capture such economic activities at a more granular level and, consequently, inform regional policies.

A Preliminary Analysis between Available and Shared Resources for the Lebanese Job Crisis

ABSTRACTThe Port of Beirut, Lebanon explosion on August 4, 2020, forced increased emigration of the Lebanese people, as they sought stability outside of their economically and politically volatile country (Farhat, 2021). Thus, families remaining in Lebanon are more dependent than ever on remittances. However, the ability of families to receive remittances is contingent on the success of those emigrating from Lebanon to gain employment. Job seekers often turn to the internet for career information from communication platforms like Reddit and dedicated job forums, like Jobs for Lebanon, among other institutional resources. This study focuses on these online institutional resources' hyperlink network, as hyperlink networks can represent a collective public good (Fu & Shumate, 2016). Data collection resulted in a network of 148 institutions. Yet with the plethora of resources available, the Lebanese community is still undergoing ineffective job searching. This preliminary research explores thse barrier between institutionally presented job resources and Lebanese job seekers by comparing the structure of the existing institutional resource network to resources shared in a leading online community. A network analysis of 148 institutions reveals: (1) unproductive job information exchange between major institutions, and (2) an opportunity for institutions to better support Lebanese job seekers.

Digitally Networked Social Services: Mapping the National Disability Insurance Scheme (NDIS) online network in Queensland, Australia

AbstractWithin growing marketisation of publicly funded services, the internet has provided new opportunities for marketing, delivery, and coordination of those services. Using web scraping and hyperlink network analysis techniques, this paper examines the ways in which organisations operating in Australia’s evolving National Disability Insurance Scheme (NDIS) system inter-connect online. Social media plays the most important role in the online network. Government agencies also play a central role, with many disability service organisations linking their web users to them. Government agency websites do not hyperlink to disability service providers, suggesting that governments do not see their role as assisting access to such services. Advocacy and peak disability organisations are important in online connections between the websites of government and service organisations. Innovative uses of the internet for online brokerage of disability services are evident. The implications of these findings for service delivery are discussed.

How deep to dig: effects of web-scraping search depth on hyperlink network analysis of environmental stewardship organizations

Social network analysis (SNA) tools and concepts are essential for addressing many environmental management and sustainability issues. One method to gather SNA data is to scrape them from environmental organizations’ websites. Web-based research can provide important opportunities to understand environmental governance and policy networks while potentially reducing costs and time when compared to traditional survey and interview methods. A key parameter is ‘search depth,’ i.e., how many connected pages within a website to search for information. Existing research uses a variety of depths and no best practices exist, undermining research quality and case study comparability. We therefore analyze how search depth affects SNA data collection among environmental organizations, if results vary when organizations have different objectives, and how search depth affects social network structure. We find that scraping to a depth of three captures the majority of relevant network data regardless of an organization’s focus. Stakeholder identification (i.e., who is in the network) may require less scraping, but this might under-represent network structure (i.e., who is connected). We also discuss how scraping web-pages of local programs of larger organizations may lead to uncertain results and how our work can combine with mixed methods approaches.

Tracing a historical development of conspiracy theory networks on the web: The hyperlink network of vaccine hesitancy on the Danish web 2006–2015

This article investigates the vast field of conspiracy theories by focusing on the example of conspiracy theories related to vaccine hesitancy. Conspiracy theories have been with us for a long time, and as any other type of semantic content they spread by travelling through media. Therefore, if one wants to understand how conspiracy theories proliferate, it is relevant to investigate the media roads by which they travel and that each offer different opportunities for establishing connections. It is obvious that within the last three decades the advent of digital media has opened up new road systems to support conspiracy theories’ getting around. This article focuses on one such road system, the World Wide Web, and how the hyperlink networks on the Danish web related to conspiracy theories and vaccine hesitancy have developed from 2006 to 2015. The article aims at (1) contributing to the development of methods that enables such a study, and (2) providing results about how these hyperlink networks have developed. The network analysis reveals that the potential exchange of ideas about vaccination between experts and non-experts is not facilitated by the media material structures in either of the years, since almost no links exist between the two actor types, at least not on the physical performative level of hyperlinks. Experts are connected, but non-experts as a whole tend to function as an archipelago of isolated islands—isolated from the experts, and by and large isolated from each other. This tendency has remained almost the same throughout the investigated period. News media that one could expect to function as brokers connecting experts and non-experts are not particularly well-connected in the network and apparently do not mediate between actor types.

Hyperlinks and media visibility on Twitter in political events in Spain: new patterns in the digital information ecology

ABSTRACT Digital environment involves numerous transformations for the media system. One of them is the process that is reconfiguring the traditional media visibility parameters from mass communication era. To study it, we use, taking an innovative approach, hyperlinks as proxy to the media visibility. Our goal is to find out the destination of the hyperlinks aimed at the media in the context of the political conversation on Twitter generated around an event of public relevance: the negotiations on the formation of the Spanish Government. The methodology is based on machine learning in a big data sample of 127.3 million tweets. This will allow us to make new contributions to how media is restructuring its social visibility as a result of integrating into the digital. The results indicate the prominence of pure players and social media platforms in the linking practices of users. By contrast, legacy media places in a secondary position. Also, geopolitical context plays a key role in conditioning the use of hyperlinks by Twitter users. Finally, our data reveal that the media have a limited capacity to determine the hyperlink network.

Quantitative and qualitative analysis of linking patterns of mainstream and partisan online news media in Central Europe

PurposePartisan 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.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueIn 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).Peer reviewThe peer review history for this article is available at the following link: https://publons.com/publon/10.1108/OIR-10-2020-0441.

Obstruction, delay, and transnationalism: Examining the online climate change counter-movement

In this article, we provide a preliminary exploration of the Climate Change Counter Movement Hyperlink Network. Recognising the international growth of the Climate Change Counter Movement, we use a hyperlink analysis to 1) identify if the counter movement uses this platform, 2) identify the structural dynamics of the hyperlink network, and 3) if and how do movement organisations connect across countries. Our findings reveal that a combination of USA and non-USA actors are operational in the hyperlink network, where climate delaying and obstruction discourse can diffuse across countries. In addition, we found cohesive subgroups illuminating an alignment of interests between think tanks across countries on climate change, a distinct role played by blogs, and a small group of connected coal-related organisations promoting information on clean coal technologies. Lastly, we observe an alignment between climate change counter movement organisations and representative organisations of the traditional Wise Use Movement. These findings provide an intriguing account of the operations of a counter movement hyperlink network, expanding our knowledge on the transmission of counter movement across countries and what this means for further developments in this area of scholarship.

Sentiment Flow Through Hyperlink Networks

How does sentiment flow through hyperlink networks? Earlier work on hyperlink networks has focused on the structure of the network, often modeling posts as nodes in a directed graph in which edges represent hyperlinks. At the same time, sentiment analysis has largely focused on classifying texts in isolation. Here we analyze a large hyperlinked network of mass media and weblog posts to determine how sentiment features of a post affect the sentiment of connected posts and the structure of the network itself. We explore the phenomena of sentiment flow through experiments on a graph containing nearly 8 million nodes and 15 million edges. Our analysis indicates that (1) nodes are strongly influenced by their immediate neighbors, (2) deep cascades lead complex but predictable lives, (3) shallow cascades tend to be objective, and (4) sentiment becomes more polarized as depth increases.

Digital humanities and web archives: Possible new paths for combining datasets

This article discusses the importance of web archives making their collections available as data and not only as sources seen through the Wayback Machine’s interface where only individual web pages are displayed. This will help unlock the full potential of the treasure trove that web archives constitute, and thereby also open up for methods from the wider field of digital humanities. Based on a case study of the entire Danish web domain .dk the article discusses methodological challenges involved in combining large extracted datasets from web archives, namely metadata about the size of websites and data about hyperlinks from the same websites. The aim is to answer the following two questions: 1) How to combine two different types of datasets extracted from a web archive, in this case the Danish Netarkivet? 2) What can the result of such a combination teach us about the structural characteristics of the Danish web domain from 2006 to 2015? The article shows that, indeed, it is possible to go beyond the Wayback Machine as the prime interface to web archives by combining two distinct datasets, and that such a venture can provide valuable knowledge about the overall structure of the Danish web domain, thus highlighting that websites of the same size tend to constitute isolated ‘link islands’, and that big websites are also the most important in the hyperlink network, which is more clearly the case in 2015 than in 2006.

Building the ‘front door’ within a web ecology: Informational governance and institutional shaping of national government webportals

Government webportals are central to governments' web strategy. They are designed to be nodal hubs, or gateways, for encountering government, and as such position government in the online world. Yet the designs of government webportals, particularly their location within wider web ecologies are scarcely studied. In additional to these web ecologies, this paper conceptualises webportals as being located within wider information and institutional ecologies. Methodologically, it comparatively examines the hyperlink structures of the national government webportals of the top ten e-government countries: Australia; Canada; Finland; France; Japan; Netherlands; New Zealand; Singapore; UK; and USA. Different ways governments approach this task are analyzed using webcrawls of the webportals and their neighboring webpages. Variations are considered in relation to the constitutional structures of the countries (i.e. unitary vs federated; centralized vs decentralized).This research highlights information referral versus information repository webportal designs, the latter of which appears to arise more in unitary and city states, than federal states. The hyperlink networks also demonstrate the important structural role of commercial social media websites in half of the countries, revealing a new interactive webportal design. Despite being constructed as whole-of-government entryways, national government webportals typically fail to connect to regional and local tiers of government. The paper provides the basis for assessing the effectiveness of different portal designs and investigating how portal designs arise out of varied government institutional settings.

True scale-free networks hidden by finite size effects

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statistical testing of the validity of power law distributions of network degrees. Specifically, we analyze by finite size scaling analysis the datasets of real networks to check whether the purported departures from power law behavior are due to the finiteness of sample size. We find that a large number of the networks follows a finite size scaling hypothesis without any self-tuning. This is the case of biological protein interaction networks, technological computer and hyperlink networks, and informational networks in general. Marked deviations appear in other cases, especially involving infrastructure and transportation but also in social networks. We conclude that underlying scale invariance properties of many naturally occurring networks are extant features often clouded by finite size effects due to the nature of the sample data.

Pathways to Teaching: The Cluttered Online Infrastructure for Potential Teacher Candidates

This paper examines a sampling of messages available to potential teacher candidates when searching online and querying, “How do I become a teacher?” Methodology used was discourse analysis of online search results using critical questions informed by Ellsworth’s (1997) notions of mode of address. Results reported here are from targeted searches on Google leading to hyperlink networks within institutional websites and social media platforms. In response to the search query on how to become a teacher, institutions present programmatic information that addresses viewers as already knowledgeable about the discourses of teacher education. Search results require browsers to sort through a cluttered landscape of requirements. Questions remain about whether or not there are comprehensible pathways presented to potential teacher candidates within one state context where teacher education enrollments are declining and teacher shortages exist across geographical regions and specific content positions like STEM education.

Toward a Transnational Information Ecology on the Right? Hyperlink Networking among Right-Wing Digital News Sites in Europe and the United States

The recent rise of a more transnationally networked political right across Europe and the United States has been accompanied by an emerging alternative digital news infrastructure through which information circulates and shared epistemologies are established. This paper examines the extent to which digital news sites on the right are interconnected within and across countries. It further explores which additional sites serve as transnationally shared reference points of such news ecology on a transnational scale. To do so, we investigate hyperlink networks between alternative right-wing online news sites (RNS) in six western democracies (Austria, Germany, United States, United Kingdom, Denmark, Sweden). Our analysis draws on hyperlink data harvested from 65 RNS for three months in 2018. The results show that RNS do establish interlinked alternative right-wing news ecologies, as they connect to likeminded RNS within and across borders. Furthermore, we see substantial variation across countries, where RNS from countries with less established alternative right-wing news infrastructure are more likely to link transnationally to RNS. The United States represents an outlier in that it features the largest and domestically most integrated network of RNS, while U.S. sites function as hubs for transnational connections from European RNS. Apart from connections between RNS, we find that legacy news media are crucial transnationally shared reference points. We conclude that rather than presenting an insulated, alternative sphere, the emerging digital news ecology on the right seeks to link up to the broader information environment across borders.