Search results

This paper evaluates the precision of four metasearch engines (MSEs) – DuckDuckGo, Dogpile, Metacrawler and Startpage, to determine which metasearch engine exhibits the highest level of precision and to identify the metasearch engine that is most likely to return the most relevant search results.

The research is divided into two parts: the first phase involves four queries categorized into two segments (4-Q-2-S), while the second phase includes six queries divided into three segments (6-Q-3-S). These queries vary in complexity, falling into three types: simple, phrase and complex. The precision, average precision and the presence of duplicates across all the evaluated metasearch engines are determined.

The study clearly demonstrated that Startpage returned the most relevant results and achieved the highest precision (0.98) among the four MSEs. Conversely, DuckDuckGo exhibited consistent performance across both phases of the study.

The study only evaluated four metasearch engines, which may not be representative of all available metasearch engines. Additionally, a limited number of queries were used, which may not be sufficient to generalize the findings to all types of queries.

The findings of this study can be valuable for accreditation agencies in managing duplicates, improving their search capabilities and obtaining more relevant and precise results. These findings can also assist users in selecting the best metasearch engine based on precision rather than interface.

The study is the first of its kind which evaluates the four metasearch engines. No similar study has been conducted in the past to measure the performance of metasearch engines.

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.

This paper constitutes the first academic study to be made of Google Discover as applied to online journalism.

This paper constitutes the first academic study to be made of Google Discover as applied to online journalism. The study involved conducting 61 semi-structured interviews with experts that are representative of a range of different professional profiles within the fields of journalism and search engine positioning (SEO) in Brazil, Spain and Greece. Based on the data collected, the authors created five semantic categories and compared the experts' perceptions in order to detect common response patterns.

This study results confirm the existence of different degrees of convergence and divergence in the opinions expressed in these three countries regarding the main dimensions of Google Discover, including specific strategies using the feed, its impact on web traffic, its impact on both quality and sensationalist content and on the degree of responsibility shown by the digital media in its use. The authors are also able to propose a set of best practices that journalists and digital media in-house web visibility teams should take into account to increase their probability of appearing in Google Discover. To this end, the authors consider strategies in the following areas of application: topics, different aspects of publication, elements of user experience, strategic analysis and diffusion and marketing.

Although research exists on the application of SEO to different areas, there have not, to date, been any studies examining Google Discover.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2022-0574

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

Rural tourism facilities in Poland were very keen on amateur websites to promote their hospitality services from 2000 to 2018. In most cases, the websites were nonprofessional, hosted on free servers and made by family members or friends of the holding. After search engine algorithms changed in 2015–2019, the websites started to go extinct on a large scale; they were deleted and often replaced with a more modern design and a commercial domain. These resources offered a rare opportunity to gain insight into rural tourism, rural changes and socioeconomic and cultural phenomena.

The paper’s objective is to demonstrate with an analysis of archived Polish rural tourism websites that digital cultural artefacts are generated in rural areas. The study was an analysis of selected development attributes of rural tourism websites found in the Internet Archive. The analysis involved those attributes that are important for determining whether a website or content can be considered digital cultural heritage assets.

The conclusions demonstrate that rural digital cultural heritage is a set of digital artefacts created in rural areas with their characteristics. Rural digital artefacts are records of ICT, infrastructure, environmental, cultural and socioeconomic changes.

The “digital assets” of rural areas are yet to be discussed in the context of rural cultural heritage, as a set of artefacts created in these areas and characteristic of them.

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

This study addresses how algorithmic recommendations and their affordances shape everyday information practices among young people.

Thematic interviews were conducted with 20 Finnish young people aged 15–16 years. The material was analysed using qualitative content analysis, with a focus on everyday information practices involving online platforms.

The key finding of the study is that the current affordances of algorithmic recommendations enable users to engage in more passive practices instead of active search and evaluation practices. Two major themes emerged from the analysis: enabling not searching, inviting high trust, which highlights the how the affordances of algorithmic recommendations enable the delegation of search to a recommender system and, at the same time, invite trust in the system, and constraining finding, discouraging diversity, which focuses on the constraining degree of affordances and breakdowns associated with algorithmic recommendations.

This study contributes new knowledge regarding the ways in which algorithmic recommendations shape the information practices in young people's everyday lives specifically addressing the constraining nature of affordances.

Cross-app interactive search has become the new normal, but the characteristics of their tactic transitions are still unclear. This study investigated the transitions of daily search tactics during the cross-app interaction search process.

In total, 204 young participants' impressive cross-app search experiences in real daily situations were collected. The search tactics and tactic transition sequences in their search process were obtained by open coding. Statistical analysis and sequence analysis were used to analyze the frequently applied tactics, the frequency and probability of tactic transitions and the tactic transition sequences representing characteristics of tactic transitions occurring at the beginning, middle and ending phases. 

Creating the search statement (Creat), evaluating search results (EvalR), evaluating an individual item (EvalI) and keeping a record (Rec) were the most frequently applied tactics. The frequency and probability of transitions differed significantly between different tactic types. “Creat? EvalR? EvalI? Rec” is the typical path; Initiate the search in various ways and modifying the search statement were highlighted at the beginning phase; iteratively creating the search statement is highlighted in the middle phase; Moreover, utilization and feedback of information are highlighted at the ending phase. 

The present study shed new light on tactic transitions in the cross-app interactive environment to explore information search behaviour. The findings of this work provide targeted suggestions for optimizing APP query, browsing and monitoring systems.

This study aims to identify user perception of different qualities of optical character recognition (OCR) in texts. The purpose of this paper is to study the effect of different quality OCR on users' subjective perception through an interactive information retrieval task with a collection of one digitized historical Finnish newspaper.

This study is based on the simulated work task model used in interactive information retrieval. Thirty-two users made searches to an article collection of Finnish newspaper Uusi Suometar 1869–1918 which consists of ca. 1.45 million autosegmented articles. The article search database had two versions of each article with different quality OCR. Each user performed six pre-formulated and six self-formulated short queries and evaluated subjectively the top 10 results using a graded relevance scale of 0–3. Users were not informed about the OCR quality differences of the otherwise identical articles.

The main result of the study is that improved OCR quality affects subjective user perception of historical newspaper articles positively: higher relevance scores are given to better-quality texts.

To the best of the authors’ knowledge, this simulated interactive work task experiment is the first one showing empirically that users' subjective relevance assessments are affected by a change in the quality of an optically read text.

This study explores the direct relationship between social media user-generated content (UGC), online search traffic and offline light vehicle sales of different models.

The long-run equilibrium relationship and short-run dynamic effects between the valence and volume of UGC, online search traffic and offline car sales are analyzed by applying the autoregressive distribution lag (ARDL) model.

The study found the following. (1) In the long-run relationship, the valence of online reviews on social media platforms is significantly negatively correlated with the sales of all models. However, in the short-run, the valence of online reviews has a significant positive correlation with all models in different lag periods. (2) The volume of online reviews is significantly positively correlated with the sales of all models in the long run. However, in the short run, the relationship between the volume of online reviews and the sales of lower-sales-volume cars is uncertain. There is a significant positive correlation between the volume of reviews and the sales of higher-sales-volume cars. (3) Online search traffic has a significantly negative correlation with the sales of all models in the long run. However, in the short run, there is no consistent conclusion on the relationship between online search traffic and car sales.

This study provides a reference for managers to use in their efforts to improve offline high-involvement product sales using online information.