scholarly journals Engagement with Search-Based Advertising on Search Engine Results Pages Varies Based on the User’s Prior Knowledge and Screen Size

2021 ◽  
Vol 16 (3) ◽  
pp. 146-148
Author(s):  
Scott Goldstein
Keyword(s):  
Eye Tracking ◽  
Search Engine ◽  
Search Engines ◽  
Information Science ◽  
Significant Negative Correlation ◽  
Screen Size ◽  
Desktop Computer ◽  
Questionnaire Score ◽  
Bottom Quartile ◽  
Level Of Knowledge

A Review of: Schultheiß, S., & Lewandowski, D. (2021). How users’ knowledge of advertisements influences their viewing and selection behavior in search engines. Journal of the Association for Information Science and Technology, 72(3), 285–301. https://doi.org/10.1002/asi.24410 Abstract Objective – To examine how users’ understanding of ads on search engine results pages (SERPs) influences their viewing and selection behaviour on computers and smartphones. Design – Mixed methods approach consisting of pre-study interview, eye-tracking experiment, and post-study questionnaire. Setting – Usability lab at a university in Germany. Subjects – 50 students enrolled at the Hamburg University of Applied Sciences and 50 non-students recruited in Hamburg. Methods – After giving informed consent and receiving payment, participants provided information on demographics as well as how they use search engines as part of a pre-study interview. For the eye-tracking experiment, each participant completed 10 tasks each on a desktop computer and smartphone. Both the device condition order and task order were randomized. Tasks were broken down into five informational tasks (e.g., how do I build a desktop computer?), three transactional tasks (e.g., how would I go about buying a refrigerator?), and two navigational tasks (e.g., I need to go to the Apple website). The software displayed clickable screenshots of SERPs, and all clicks were recorded. iMotions eye-tracking software recorded eye fixations on areas of the page featuring organic search results and paid ads. A post-experiment questionnaire asked participants about Google’s business model and probed them about the extent to which they were able to differentiate between organic results and ads. Answers to the questionnaire were weighted and normalized to form a 0–100 scale. Main Results – The first set of research hypotheses examining the correlation between participants’ knowledge of ads and viewing and clicking behaviour was partially confirmed. There was no significant correlation between participants’ questionnaire score and visual fixations on ads, but there was a significant negative correlation between questionnaire score and the number of clicks on ads. Users with questionnaire scores in the bottom quartile paid significantly less attention to organic results than those in the top quartile, but users in the top quartile still fixated on ads and did so comparably to users in the bottom quartile. The second set of research hypotheses examining the relationship between viewing and clicking behaviour and device (desktop versus mobile) was also partially confirmed. Users on a smartphone had significantly higher fixation rates on ads than users on a desktop computer, although click rates on ads did not differ significantly between the two conditions. Conclusion – Knowledge about ads on SERPs influences selection behaviour. Users with a low level of knowledge on search advertising are more likely to click on ads than those with a high level of knowledge. Users on smartphones are also more likely to pay visual attention to ads, probably because the smaller screen size narrows content “above the fold.”

scholarly journals Eye-Tracking Studies of Web Search Engines: A Systematic Literature Review

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 300 ◽  
Author(s):  
Artur Strzelecki
Keyword(s):  
Content Analysis ◽  
Literature Review ◽  
Eye Tracking ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Web Searches ◽  
Research Questions ◽  
Web Search Engines ◽  
Element Matrix

This paper analyzes peer-reviewed empirical eye-tracking studies of behavior in web search engines. A framework is created to examine the effectiveness of eye-tracking by drawing on the results of, and discussions concerning previous experiments. Based on a review of 56 papers on eye-tracking for search engines from 2004 to 2019, a 12-element matrix for coding procedure is proposed. Content analysis shows that this matrix contains 12 common parts: search engine; apparatus; participants; interface; results; measures; scenario; tasks; language; presentation, research questions; and findings. The literature review covers results, the contexts of web searches, a description of participants in eye-tracking studies, and the types of studies performed on the search engines. The paper examines the state of current research on the topic and points out gaps in the existing literature. The review indicates that behavior on search engines has changed over the years. Search engines’ interfaces have been improved by adding many new functions and users have moved from desktop searches to mobile searches. The findings of this review provide avenues for further studies as well as for the design of search engines.

scholarly journals The Matter of Chance: Auditing Web Search Results Related to the 2020 U.S. Presidential Primary Elections Across Six Search Engines

2021 ◽  
pp. 089443932110068
Author(s):  
Aleksandra Urman ◽  
Mykola Makhortykh ◽  
Roberto Ulloa
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Large Scale ◽  
Web Search ◽  
Primary Elections ◽  
Virtual Agents ◽  
Search Results ◽  
Presidential Primary ◽  
Large Scale Analysis ◽  
Algorithmic Information

We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default—that is nonpersonalized—conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale analysis of algorithmic information curation in a controlled environment. Specifically, we look at the text search results for “us elections,” “donald trump,” “joe biden,” “bernie sanders” queries on Google, Baidu, Bing, DuckDuckGo, Yahoo, and Yandex, during the 2020 primaries. Our findings indicate substantial differences in the search results between search engines and multiple discrepancies within the results generated for different agents using the same search engine. It highlights that whether users see certain information is decided by chance due to the inherent randomization of search results. We also find that some search engines prioritize different categories of information sources with respect to specific candidates. These observations demonstrate that algorithmic curation of political information can create information inequalities between the search engine users even under nonpersonalized conditions. Such inequalities are particularly troubling considering that search results are highly trusted by the public and can shift the opinions of undecided voters as demonstrated by previous research.

scholarly journals Examining and Fine-tuning the Selection of Glycan Compositions with GlyConnect Compozitor

2020 ◽  
Vol 19 (10) ◽  
pp. 1602-1618 ◽  
Author(s):  
Thibault Robin ◽  
Julien Mariethoz ◽  
Frédérique Lisacek
Keyword(s):  
Search Engine ◽  
Posttranslational Modifications ◽  
Search Engines ◽  
Web Application ◽  
Contextual Information ◽  
Fine Tuning ◽  
Data Sources ◽  
Web Interface ◽  
Definition Of ◽  
Selection Of

A key point in achieving accurate intact glycopeptide identification is the definition of the glycan composition file that is used to match experimental with theoretical masses by a glycoproteomics search engine. At present, these files are mainly built from searching the literature and/or querying data sources focused on posttranslational modifications. Most glycoproteomics search engines include a default composition file that is readily used when processing MS data. We introduce here a glycan composition visualizing and comparative tool associated with the GlyConnect database and called GlyConnect Compozitor. It offers a web interface through which the database can be queried to bring out contextual information relative to a set of glycan compositions. The tool takes advantage of compositions being related to one another through shared monosaccharide counts and outputs interactive graphs summarizing information searched in the database. These results provide a guide for selecting or deselecting compositions in a file in order to reflect the context of a study as closely as possible. They also confirm the consistency of a set of compositions based on the content of the GlyConnect database. As part of the tool collection of the Glycomics@ExPASy initiative, Compozitor is hosted at https://glyconnect.expasy.org/compozitor/ where it can be run as a web application. It is also directly accessible from the GlyConnect database.

Search Engine Update

2001 ◽  
Vol 1 (3) ◽  
pp. 28-31 ◽  
Author(s):  
Valerie Stevenson
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Search Strategy ◽  
Search Strategies ◽  
Boolean Logic ◽  
Web Searches ◽  
Search Techniques ◽  
Looking Back ◽  
The Web

Looking back to 1999, there were a number of search engines which performed equally well. I recommended defining the search strategy very carefully, using Boolean logic and field search techniques, and always running the search in more than one search engine. Numerous articles and Web columns comparing the performance of different search engines came to different conclusions on the ‘best’ search engines. Over the last year, however, all the speakers at conferences and seminars I have attended have recommended Google as their preferred tool for locating all kinds of information on the Web. I confess that I have now abandoned most of my carefully worked out search strategies and comparison tests, and use Google for most of my own Web searches.

Automatic Keyword Extraction Algorithm and Implementation

2010 ◽  
Vol 44-47 ◽  
pp. 4041-4049 ◽  
Author(s):  
Hong Zhao ◽  
Chen Sheng Bai ◽  
Song Zhu
Keyword(s):  
Search Engine ◽  
Word Frequency ◽  
Search Engines ◽  
Keyword Extraction ◽  
Web Page ◽  
C Language ◽  
Search Engine Optimization ◽  
Page Ranking ◽  
Extraction Algorithm ◽  
A Site

Search engines can bring a lot of benefit to the website. For a site, each page’s search engine ranking is very important. To make web page ranking in search engine ahead, Search engine optimization (SEO) make effect on the ranking. Web page needs to set the keywords as “keywords" to use SEO. The paper focuses on the content of a given word, and extracts the keywords of each page by calculating the word frequency. The algorithm is implemented by C # language. Keywords setting of webpage are of great importance on the information and products

Website removal from search engines due to copyright violation

2019 ◽  
Vol 71 (1) ◽  
pp. 54-71 ◽  
Author(s):  
Artur Strzelecki
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Design Methodology ◽  
Global Analysis ◽  
Domain Name ◽  
Content Type ◽  
Search Results ◽  
Internet Users ◽  
Copyright Violation

Purpose The purpose of this paper is to clarify how many removal requests are made, how often, and who makes these requests, as well as which websites are reported to search engines so they can be removed from the search results. Design/methodology/approach Undertakes a deep analysis of more than 3.2bn removed pages from Google’s search results requested by reporting organizations from 2011 to 2018 and over 460m removed pages from Bing’s search results requested by reporting organizations from 2015 to 2017. The paper focuses on pages that belong to the .pl country coded top-level domain (ccTLD). Findings Although the number of requests to remove data from search results has been growing year on year, fewer URLs have been reported in recent years. Some of the requests are, however, unjustified and are rejected by teams representing the search engines. In terms of reporting copyright violations, one company in particular stands out (AudioLock.Net), accounting for 28.1 percent of all reports sent to Google (the top ten companies combined were responsible for 61.3 percent of the total number of reports). Research limitations/implications As not every request can be published, the study is based only what is publicly available. Also, the data assigned to Poland is only based on the ccTLD domain name (.pl); other domain extensions for Polish internet users were not considered. Originality/value This is first global analysis of data from transparency reports published by search engine companies as prior research has been based on specific notices.

scholarly journals IMPLEMENTASI ALGORITMA GOOGLE LATENT SEMANTIC DISTANCE UNTUK EKSTRAKSI RANGKAIAN KATA KUNCI ARTIKEL JURNAL ILMIAH

2018 ◽  
Vol 2 (2) ◽  
pp. 186
Author(s):  
Novario Jaya Perdana
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Semantic Distance ◽  
Relevant Information ◽  
High Accuracy ◽  
Hard Work ◽  
The Internet ◽  
Search Results ◽  
Search Result

The accuracy of search result using search engine depends on the keywords that are used. Lack of the information provided on the keywords can lead to reduced accuracy of the search result. This means searching information on the internet is a hard work. In this research, a software has been built to create document keywords sequences. The software uses Google Latent Semantic Distance which can extract relevant information from the document. The information is expressed in the form of specific words sequences which could be used as keyword recommendations in search engines. The result shows that the implementation of the method for creating document keyword recommendation achieved high accuracy and could finds the most relevant information in the top search results.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Tom Kralidis ◽  
Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Search Engines ◽  
Spatial Information ◽  
Text Search ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Database Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software component of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information. A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogs and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalog, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Tom Kralidis ◽  
Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Search Engines ◽  
Spatial Information ◽  
Data Infrastructure ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software components of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information. A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogues and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalogue, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Tom Kralidis ◽  
Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Search Engines ◽  
Spatial Information ◽  
Data Infrastructure ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software components of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information. A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogues and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalogue, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.

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