Search results

This study aims to develop an associative text analyzer (ATA) to support users in quickly grasping and interpreting the content of large amounts of text through text association recommendations, facilitating the identification of the contextual relationships between people, events, organization and locations for digital humanities. Additionally, by providing text summaries, the tool allows users to link between distant and close readings, thereby enabling more efficient exploration of related texts.

To verify the effectiveness of this tool in supporting exploration of historical texts, this study uses a counterbalanced design to compare the use of the digital humanities platform for Mr. Lo Chia-Lun’s Writings (DHP-LCLW) with and without the ATA to assist in exploring different aspects of text. The study investigated whether there were significant differences in effectiveness for exploring textual contexts and technological acceptance as well as used semi-structured in-depth interviews to understand the research participants’ viewpoints and experiences with the ATA.

The results of the experiment revealed that the effectiveness of text exploration using the DHP-LCLW with and without the ATA varied significantly depending on the topic of the text being explored. The DHP-LCLW with the ATA was found to be more suitable for exploring historical texts, while the DHP-LCLW without the ATA was more suitable for exploring educational texts. The DHP-LCLW with the DHP-LCLW was found to be significantly more useful in terms of perceived usefulness than the DHP-LCLW without the ATA, indicating that the research participants believed the ATA was more effective in helping them efficiently grasp the related texts and topics during text exploration.

The study’s practical implications lie in the development of an ATA for digital humanities, offering a valuable tool for efficiently exploring historical texts. The ATA enhances users’ ability to grasp and interpret large volumes of text, facilitating contextual relationship identification. Its practical utility is evident in the improved effectiveness of text exploration, particularly for historical content, as indicated by users’ perceived usefulness.

This study proposes an ATA for digital humanities, enhancing text exploration by offering association recommendations and efficient linking between distant and close readings. The study contributes by providing a specialized tool and demonstrating its perceived usefulness in facilitating efficient exploration of related texts in digital humanities.

Knowledge graphs (KGs) are structured knowledge bases that represent real-world entities and are used in a variety of applications. Many of them are created and curated from a combination of automated and manual processes. Microdata embedded in Web pages for purposes of facilitating indexing and search engine optimization are a potential source to augment KGs under some assumptions of complementarity and quality that have not been thoroughly explored to date. In that direction, this paper aims to report results on a study that evaluates the potential of using microdata extracted from the Web to augment the large, open and manually curated Wikidata KG for the domain of touristic information. As large corpora of Web text is currently being leveraged via large language models (LLMs), these are used to compare the effectiveness of the microdata enhancement method.

The Schema.org taxonomy was used as the source to determine the annotation types to be collected. Here, the authors focused on tourism-related pages as a case study, selecting the relevant Schema.org concepts as point of departure. The large CommonCrawl resource was used to select those annotations from a large recent sample of the World Wide Web. The extracted annotations were processed and matched with Wikidata to estimate the degree to which microdata produced for SEO might become a valuable resource to complement KGs or vice versa. The Web pages themselves can also serve as a context to produce additional metadata elements using them as context in pipelines of an existing LLMs. That way, both the annotations and the contents itself can be used as sources.

The samples extracted revealed a concentration of metadata annotations in only a few of the relevant Schema.org attributes and also revealed the possible influence of authoring tools in a significant fraction of microdata produced. The analysis of the overlapping of attributes in the sample with those of Wikidata showed the potential of the technique, limited by the disbalance of the presence of attributes. The combination of those with the use of LLMs to produce additional annotations demonstrates the feasibility of the approach in the population of existing Wikidata locations. However, in both cases, the effectiveness appears to be lower in the cases of less content in the KG, which are arguably the most relevant when considering the scenario of an automated population approach.

The research reports novel empirical findings on the way touristic annotations with a SEO orientation are being produced in the wild and provides an assessment of their potential to complement KGs, or reuse information from those graphs. It also provides insights on the potential of using LLMs for the task.

This article presents two Brazilian Portuguese corpora collected from different media concerning public security issues in a specific location. The primary motivation is supporting analyses, so security authorities can make appropriate decisions about their actions.

The corpora were obtained through web scraping from a newspaper's website and tweets from a Brazilian metropolitan region. Natural language processing was applied considering: text cleaning, lemmatization, summarization, part-of-speech and dependencies parsing, named entities recognition, and topic modeling.

Several results were obtained based on the methodology used, highlighting some: an example of a summarization using an automated process; dependency parsing; the most common topics in each corpus; the forty named entities and the most common slogans were extracted, highlighting those linked to public security.

Some critical tasks were identified for the research perspective, related to the applied methodology: the treatment of noise from obtaining news on their source websites, passing through textual elements quite present in social network posts such as abbreviations, emojis/emoticons, and even writing errors; the treatment of subjectivity, to eliminate noise from irony and sarcasm; the search for authentic news of issues within the target domain. All these tasks aim to improve the process to enable interested authorities to perform accurate analyses.

The corpora dedicated to the public security domain enable several analyses, such as mining public opinion on security actions in a given location; understanding criminals' behaviors reported in the news or even on social networks and drawing their attitudes timeline; detecting movements that may cause damage to public property and people welfare through texts from social networks; extracting the history and repercussions of police actions, crossing news with records on social networks; among many other possibilities.

The work on behalf of the corpora reported in this text represents one of the first initiatives to create textual bases in Portuguese, dedicated to Brazil's specific public security domain.

Evidence-based practice is a professional standard for occupational therapists, but limited time, resources and knowledge challenge its implementation. This study aims to identify what free evidence summary sources (FESS) can be found through a simple online search, related to child/youth interventions surrounding cerebral palsy (CP), autism spectrum disorder (ASD), developmental coordination disorder (DCD), mental health or attention-deficit/hyperactivity disorder (MH/ADHD). Evidence summaries share research in concise, time-efficient manners.

An internet-based scoping review was conducted between February 2022 and July 2022, using Google, and known evidence summary producers. Evidence summaries meeting the inclusion criteria were located and catalogued. Type of agency, target audiences, purpose and distribution of evidence summaries related to diagnosis were identified for each FESS.

Ten FESS were found, which produced 113 intervention-focused evidence summaries within the past 10 years. These FESS were aimed at a variety of target audiences: service providers, service users, parents/families, researchers and commissioners, and were produced primarily by non-profit/charity organisations (6 of 10) who were trying to fill a gap in evidence. Forty-eight evidence summaries were related to ASD, 34 to CP, 29 to MH/ADHD and two to DCD.

A catalogue of FESS that exist online was produced, to support evidence-based practice for paediatric occupational therapists with limited resources, and may support improved health promotion and informed decision-making for service users. No consistent framework for FESS evidence summaries exists at this time.

The use of brand slogans that represent brand concepts on app launch pages can improve user brand impressions. The purpose of this paper is to investigate the impact of using animated or static spokes-characters with brand slogans on app launch pages.

Using the theory of attention selection, the authors conducted two experiments to study the boundary and mediation path of the influence of the motion attributes of spokes-characters (static vs animated) on brand memory based on app launch time (3 s vs 5 s), user engagement with spokes-characters and the level of attention to brand slogans.

Study 1 explores the effect of the interaction between launch time and the motion attributes of spokes-characters on brand memory. The results show that when the launch time of the app is 3 s, the advertisement memory effect of using a static spokes-character is better than that of using an animated spokes-character; when the launch time of the app is 5 s, the advertisement memory effect of using an animated spokes-character is better than that of using a static spokes-character. Study 2 shows that user engagement with spokes-characters and the level of attention given to brand slogans play a continuous mediating role in the effect of the interaction between launch time and the motion attributes of spokes-characters on brand memory.

This paper contributes to the marketing literature by expanding the knowledge of spokes-characters and animated visual images, providing new insights for future research.

This study aims to discover how domain familiarity and language affect the cognitive load and the strategies applied for the evaluation of search engine results pages (SERP).

This study used an experimental research design. The pattern of the experiment was based upon repeated measures design. Each student was given four SERPs varying in two dimensions: language and content. The criteria of students to decide on the three best links within the SERP, the reasoning behind their selection, and their perceived cognitive load of the given task were the repeated measures collected from each participant.

The evaluation criteria changed according to the language and task type. The cognitive load was reported higher when the content was presented in English or when the content was academic. Regarding the search strategies, a majority of students trusted familiar sources or relied on keywords they found in the short description of the links. A qualitative analysis showed that students can be grouped into different types according to the reasons they stated for their choices. Source seeker, keyword seeker and specific information seeker were the most common types observed.

This study has an international scope with regard to data collection. Moreover, the tasks and findings contribute to the literature on information literacy.

The purpose of this paper is to examine the impact of affiliate marketing strategies as a tool for increasing customers' engagement and vulnerability over financial services. This is attempted by examining the connection between affiliate marketing factors and customers' brand engagement and vulnerability metrics.

The authors developed a three-staged methodological context, based on the 7 most known centralized payment network (CPN) firms' website analytical data, which begins with linear regression analysis, followed by hybrid modeling (agent-based and dynamic models), so as to simulate brand engagement and vulnerability factors' variation in a 180-day period. The deployed context ends by applying the cognitive modeling method of producing heatmaps and facial analysis of CPN websites to the selected 47 vulnerable website customers, for gathering more insights into their brand engagement.

Throughout the simulation results of the study, it becomes clear that a higher number of backlinks and referral domains tend to increase CPN firms' brand-engaged and vulnerable customers.

From the simulation modeling process, the implication for backlinks and referral domains as factors that enhance website customers' brand engagement and vulnerability has been highlighted. A higher number of brand-engaged website customers could mean that vulnerable categories of customers would be impacted by CPNs' affiliate marketing. Improving those customers' knowledge of the financial services utility is of utmost importance.

The outcomes of the research indicate that online banking service providers can increase their customers' engagement with their brands by adopting affiliate marketing techniques. To avoid the increase in customers' vulnerability, marketers should aim to apply affiliate marketing strategies to domains relevant to the provided financial services.

The paper's outcomes provide a new approach to the literature, where the website customer's brand engagement comes out as a valuable metric for estimating online banking sector customers' vulnerability.

The purpose of this study was to examine consumer data acquired by branded prescription drug websites and the ethics of privacy related to the interconnected web of personal information accessed, packaged and resold by tracker technologies.

The research used the DMI Tracker Tool to collect data on the top 17 branded prescription drug websites, with a specific interest in the tracker technologies embedded in those websites. That data was analyzed using Gephi, an open-source data visualization tool, to map the network of trackers embedded in those branded prescription drug websites.

Findings visualize the interconnections between tracker technologies and prescription drug websites that undergird a system of personal data acquisition and programmatic advertising vehicles that serve the interests of prescription drug marketers and Big Tech. Based on the theory of platform ethics, the study demonstrated the presence of a technostructural ecosystem dominated by Big Tech, a system that goes unseen by consumers and serves the interests of advertisers and resellers of consumer data.

The 17 websites used in this study were limited to the top-selling prescription drugs or those with the highest ad expenditures. As such this study is not based on a random sampling of branded prescription drug websites. The popularity of these prescription drugs or the expanse of advertising associated with the drugs makes them appropriate to study the presence of tracking devices that collect data from consumers and serve advertising to them. It is also noted that websites are dynamic spaces, and some trackers within their infrastructures are apt to change over time.

Branded prescription drug information has over the past three decades become part of consumers’ routine search for information regarding what ails them. As drug promotion moved from print to TV and the Web, searching for drug information has become a part of everyday life. The implications of embedded trackers on branded prescription drug websites are the subject of this research.

This study has significant social implications as consumers who are searching for information regarding prescription medications may not want drug companies tracking them in a way that many perceive to be an invasion of privacy. Yet, as the Web is dominated by Big Tech, web developers have little choice but to remain a part of this technostructural ecosystem.

This study sheds light on branded prescription drug websites, exploring the imbalance between the websites under study, Big Tech and consumers who lack awareness of the system that operates backstage.

The objective of this paper is to further the understanding of netnography as a research method for supply chain academics. Netnography is a method for gathering and gaining insight from industry-specific online communities. We prescribe that viewing netnography through the lens of the supply chain will permit researchers to explore, discover, understand, describe or report concepts or phenomena that have previously been studied via survey research or quantitative modeling.

To introduce netnography to supply chain research, we propose a framework to guide how netnography can be adopted and used. Definitions and directions are provided, highlighting some of the practices within netnographic research.

Netnography provides the researcher with another avenue to pursue answers to research questions, either alone or in conjunction with the dominant methods of survey research and quantitative modeling. It provides another tool in the researchers’ toolbox to engage practitioners in the field.

The development of netnography as a research method is associated with Robert Kozinets. He developed the method to study online communities in consumer behavior. We justify why this method can be applied to supply chain research, how to collect data and provide research examples of its use. This technique has room to grow as a supply chain research method.

The sharing economy, supported by digital platforms, efficiently matches the demand and supply of underused resources. Expanding globally and impacting different industries is offering a new path to sustainable resource consumption. The United Nations endorsed the sustainable development goals (SDGs), responding to a global call to end poverty, protect the environment and ensure that by 2030, everyone lives in peace and prosperity. Researchers have linked the sharing economy with SGDs, and extensive efforts have been exerted to quantify its impact.

Due to its evolving nature, especially in developing countries, there is a need for research to assess its promises and challenges from the SDG perspective. This research fills in this gap and contributes to the sharing economy studies by exploring its evolution within the framework of sustainable development goals, followed by an assessment of various methodologies for measuring the sharing economy and highlighting the significance of the web mining technique.

The proper implementation of this decentralized business model within a country is encouraging optimal resource use, lowering energy consumption and increasing long-term economic development. The sharing economy is a disruptive force that addresses the pillars of sustainability.

The research holds importance in addressing the achievement of the SDGs through the sharing economy, necessitating focus from policymakers and scholarly discourse on its merits. The transformative impact of the sharing economy poses questions about its encouragement or regulation, with the potential to disrupt established monopolies and possibly create new ones. Its successful implementation underscores the significance of effective data sharing and governance.