Retrieval of Personal Public Data on Social Networks

2013 ◽  
pp. 137-160
Author(s):  
Francesca Carmagnola ◽  
Francesco Osborne ◽  
Ilaria Torre
Keyword(s):  
Social Networks ◽  
Search Engine ◽  
Search Engines ◽  
Simulation Analysis ◽  
Software Agents ◽  
User Perception ◽  
Public Data ◽  
User Data ◽  
People Search ◽  
Different Sources

In this chapter, the authors analyze the risks for privacy coming from the distribution of user data over several social networks. Specifically, they focus on risks concerning the possibility to aggregate user data discovered on different sources into a single more complete profile, which makes possible to infer other data, likely set as private by the user. In order to show how it is possible to human users as well as to software agents crawling social networks, identifying users, linking their profiles and aggregating their data, the authors describe the prototype of a search engine they developed. The authors also present a simulation analysis to show the retrievability of user data by using a combination of people search engines and they provide statistics on the user perception on this issue.

User Perception Affects Search Engine Advertising Avoidance: Moderating Role of User Characteristics

2019 ◽  
Vol 47 (4) ◽  
pp. 1-12 ◽  
Author(s):  
Yujie Li
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Positive Impact ◽  
Television Advertising ◽  
Location Awareness ◽  
User Perception ◽  
Monthly Income ◽  
User Characteristics ◽  
Negative Experience ◽  
Search Engine Advertising

Researchers have examined avoidance of traditional media advertising (e.g., television advertising) and general Internet advertising (e.g., banner advertising), but less attention has been paid to search engine advertising (SEA) avoidance, particularly in the Chinese context. Therefore, I analyzed the effects of 3 components of user perception of SEA (perceived goal impediment, perceived advertising clutter, and prior negative experience) and 2 components of user characteristics (monthly income and advertising location awareness) on SEA avoidance in a sample of 348 working professionals who use Chinese search engines. Results showed that user perception had a significantly positive impact on SEA avoidance, monthly income attenuated the positive impact of perceived advertising clutter but intensified the positive impact of prior negative experience on SEA avoidance, and advertising location awareness enhanced the positive impact of perceived advertising clutter on SEA avoidance. Implications of the findings for effective advertising on search engines are discussed.

Search Engine as a mediating technology of organization

2019 ◽  
pp. 411-429
Author(s):  
Renée Ridgway
Keyword(s):  
Machine Learning ◽  
Search Engine ◽  
Search Engines ◽  
Relational Databases ◽  
Machine Learning Algorithms ◽  
Online Information ◽  
Advertising Agencies ◽  
User Data ◽  
History Of ◽  
Personalized Advertisement

Search engines have become the technological and organizational means to navigate, filter, and rank online information for users. During the seventeenth to nineteenth centuries in Europe, the ‘pre-history’ of search engines were the ‘bureau d’adresse’ or ‘address office’ that provided information and services to clients as they gathered data. Registers, censuses, and archives eventually shifted to relational databases owned by commercial platforms, advertising agencies cum search engines that provide non-neutral answers in exchange for user data. With ‘cyberorganization’, personalized advertisement, machine-learning algorithms, and ‘surveillance capitalism’ organize the user through their ‘habit’ of search. However, there are alternatives such as the p2p search engine YaCy and anonymity browsing with Tor.

Provenance-Aware Semantic Search Engines Based On Data Integration Systems

2014 ◽  
Vol 4 (2) ◽  
pp. 1-30 ◽  
Author(s):  
Domenico Beneventano ◽  
Sonia Bergamaschi
Keyword(s):  
Data Integration ◽  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Semantic Search ◽  
Functional Features ◽  
Processing Engine ◽  
Different Sources ◽  
Semantic Search Engine ◽  
Relevant Class

Search engines are common tools for virtually every user of the Internet and companies, such as Google and Yahoo!, have become household names. Semantic Search Engines try to augment and improve traditional Web Search Engines by using not just words, but concepts and logical relationships. Given the openness of the Web and the different sources involved, a Web Search Engine must evaluate quality and trustworthiness of the data; a common approach for such assessments is the analysis of the provenance of information. In this paper a relevant class of Provenance-aware Semantic Search Engines, based on a peer-to-peer, data integration mediator-based architecture is described. The architectural and functional features are an enhancement with provenance of the SEWASIE semantic search engine developed within the IST EU SEWASIE project, coordinated by the authors. The methodology to create a two level ontology and the query processing engine developed within the SEWASIE project, together with provenance extension are fully described.

scholarly journals Data, Their Relevance to Competition and Search Engines

2021 ◽  
Vol 15 (1) ◽  
pp. 119-140
Author(s):  
Rastislav Funta
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Business Models ◽  
Search Algorithm ◽  
Decisive Role ◽  
Web Pages ◽  
Abusive Behavior ◽  
Digital Business Models ◽  
User Data

A special feature of digital markets and digital business models is the high importance of (user) data. The control and the ability to analyze large amounts of data (big data) can create competitive advantage. Thus, the importance of data for the economic success of companies should be given more consideration in competition law proceedings. In search services competition, the quality factor plays a decisive role, since the expected quality of the search results determines which search engine will be used by users. Since search engines can influence the retrievability of web pages for users, preference of own search services in the web index may constitute an abusive behavior of a dominant search engine. The purpose of this paper is to provide answers on questions, among other, whether a regulation aimed at preventing abuses is necessary or whether an obligation to publish the search algorithm may be advocated.

Online Sponsored Search Budget Allocation across Search Engines: A Simulation Analysis

2014 ◽  
Vol 577 ◽  
pp. 926-930
Author(s):  
Bao Jian Zhou ◽  
Wei Qi ◽  
Li Gang Chen ◽  
Qiang Ye
Keyword(s):  
Decision Making ◽  
Search Engine ◽  
Search Engines ◽  
Simulation Analysis ◽  
Budget Allocation ◽  
Quality Score ◽  
Sponsored Search ◽  
Simulation Framework ◽  
Viable Option ◽  
Problem Model

Recently, sponsored search has been rapidly growing which increase tremendous interests in improving performance in search engine marketplace. The complexity of market dynamics makes it difficult for advertisers to maximizing the effect of advertising. Simulation analysis is a more viable option than real world testing especially in fast accomplishing different experiments and effectively prompting decision making supports. In this paper, the sponsored search budget allocation problem model integrated with quality score for single search engine has been explored and then extended to multiple quality-based search engines. Also, several advertising policies have been proposed and verified under the general simulation framework in both single and multiple search engine scenarios.

Quality Assessment of Health Information about Scaphoid Fracture in Chinese Websites (Preprint)

2019 ◽  
Author(s):  
Yaobin Yin ◽  
Jianguang Ji ◽  
Peng Lu ◽  
Wenyao Zhong ◽  
Liying Sun ◽  
...  
Keyword(s):  
Social Networks ◽  
Health Information ◽  
Search Engines ◽  
Medical Information ◽  
Scaphoid Fracture ◽  
Family Members ◽  
Online Information ◽  
Specific Content ◽  
The Mean

BACKGROUND With online health information becoming increasingly popular among patients and their family members, concerns have been raised about the accuracy from the websites. OBJECTIVE We aimed to evaluate the overall quality of the online information about scaphoid fracture obtained from Chinese websites using the local search engines. METHODS We conducted an online search using the keyword “scaphoid fracture” from the top 5 search engines in China, i.e. Baidu, Shenma, Haosou, Sougou and Bing, and gathered the top ranked websites, which included a total of 120 websites. Among them, 81 websites were kept for further analyses by removing duplicated and unrelated one as well as websites requiring payment. These websites were classified into four categories, including forum/social networks, commercials, academics and physician’s personals. Health information evaluation tool DISCERN and Scaphoid Fracture Specific Content Score (SFSCS) were used to assess the quality of the websites. RESULTS Among the 81 Chinese websites that we studied, commercial websites were the most common one accounting more than half of all websites. The mean DISCERN score of the 81 websites was 25.56 and no website had a score A (ranging from 64 to 80).The mean SFSCS score was 10.04 and no website had a score A (range between 24 and 30). In addition, DISCERN and SFSCS scores from academic and physician’s websites were significantly higher than those from the forum/social networks and commercials. CONCLUSIONS The overall quality of health information obtained from Chinese websites about scaphoid fracture was very low, suggesting that patients and their family members should be aware such deficiency and pay special attentions for the medical information obtained by using the current search engines in China.

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.

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