scholarly journals Tool to Retrieve Less-Filtered Information from the Internet

Information ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 65
Author(s):  
Yuta Nemoto ◽  
Vitaly Klyuev

While users benefit greatly from the latest communication technology, with popular platforms such as social networking services including Facebook or search engines such as Google, scientists warn of the effects of a filter bubble at this time. A solution to escape from filtered information is urgently needed. We implement an approach based on the mechanism of a metasearch engine to present less-filtered information to users. We develop a practical application named MosaicSearch to select search results from diversified categories of sources collected from multiple search engines. To determine the power of MosaicSearch, we conduct an evaluation to assess retrieval quality. According to the results, MosaicSearch is more intelligent compared to other general-purpose search engines: it generates a smaller number of links while providing users with almost the same amount of objective information. Our approach contributes to transparent information retrieval. This application helps users play a main role in choosing the information they consume.

Author(s):  
Cheng-Jye Luh ◽  
Lin-Chih Chen

This chapter presents an intelligent metasearch engine that can recommend a user’s next hyperlink access and relevant paragraphs extracted from metasearch results. The proposed design is based on the primacy effect of browsing behavior, that users prefer top ranking items in search results. Three search methods were implemented in this engine. First, the search engine vector voting (SVV) method rearranges search results gathered from six well-known search engines according to their weights obtained from user behavior function. The hyperlink prediction (HLP) method then arranges the most likely accessed hyperlinks from the URLs in SVV search results. Finally, the page clipping synthesis (PCS) method extracts relevant paragraphs from the HLP search results. A user study indicated that users are more satisfied with the proposed search methods than with general search engines. Moreover, performance measure results confirmed that the proposed search methods outperform other metasearch and search engines.


2019 ◽  
Author(s):  
Jungu Kim ◽  
Su Cheol Kim ◽  
Jaegwon Jeong ◽  
Myeong Gyu Kim

BACKGROUND Methylphenidate, a stimulant used to treat attention deficit hyperactivity disorder (ADHD), has the potential for nonmedical uses such as study and recreation. In the era of active use of social networking services (SNSs), experience with the nonmedical use or side effects of methylphenidate might be shared on Twitter. OBJECTIVE To analyze monthly tweets about methylphenidate, its nonmedical use and side effects, and user sentiments about methylphenidate. METHODS Tweets mentioning methylphenidate from August 2018 to July 2019 were collected using search terms for methylphenidate and its brand names. Only tweets written in English were included. The monthly number of tweets about methylphenidate and the number of tweets containing keywords related to the nonmedical use and side effects of methylphenidate were analyzed. Precision was calculated as the number of true nonmedical use or side effects divided by the number of tweets containing each keywords. Sentiment analysis was conducted using the text and emoji in tweets, and tweets were categorized as very negative (less than -3), negative (-3 to -1), neutral (0), positive (1 to 3), or very positive (more than 3), depending on the sentiment score. RESULTS A total of 4,169 tweets were ultimately selected for analysis. The number of tweets per month was lowest in August (n=264) and highest in May (n=435). There were 292 (7.0%) tweets about nonmedical uses of methylphenidate. Among those, 200 (4.8%) described use for studying, and 15 (0.4%) described use for recreation. In 91 (2.2%) tweets, snorting methylphenidate was mentioned. Side effects of methylphenidate, mainly poor appetite (n=74, 1.8%) and insomnia (n=54, 1.3%), were reported in 316 (7.6%) tweets. The average sentiment score was 0.027 ± 1.475, and neutral tweets were the most abundant (n=1,593, 38.2%). CONCLUSIONS Tweets about methylphenidate were most abundant in May, mentioned nonmedical use for study or recreation, and contained information about side effects. Analysis of Twitter has the advantage of saving the cost and time needed to conduct a survey, and could help identify nonmedical uses and side effects of drugs.


2021 ◽  
pp. 089443932110068
Author(s):  
Aleksandra Urman ◽  
Mykola Makhortykh ◽  
Roberto Ulloa

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.


2021 ◽  
Vol 11 (15) ◽  
pp. 7063
Author(s):  
Esmaeel Rezaee ◽  
Ali Mohammad Saghiri ◽  
Agostino Forestiero

With the increasing growth of different types of data, search engines have become an essential tool on the Internet. Every day, billions of queries are run through few search engines with several privacy violations and monopoly problems. The blockchain, as a trending technology applied in various fields, including banking, IoT, education, etc., can be a beneficial alternative. Blockchain-based search engines, unlike monopolistic ones, do not have centralized controls. With a blockchain-based search system, no company can lay claims to user’s data or access search history and other related information. All these data will be encrypted and stored on a blockchain. Valuing users’ searches and paying them in return is another advantage of a blockchain-based search engine. Additionally, in smart environments, as a trending research field, blockchain-based search engines can provide context-aware and privacy-preserved search results. According to our research, few efforts have been made to develop blockchain use, which include studies generally in the early stages and few white papers. To the best of our knowledge, no research article has been published in this regard thus far. In this paper, a survey on blockchain-based search engines is provided. Additionally, we state that the blockchain is an essential paradigm for the search ecosystem by describing the advantages.


2020 ◽  
Vol 69 (8/9) ◽  
pp. 717-736
Author(s):  
Małgorzata Kowalska-Chrzanowska ◽  
Przemysław Krysiński

Purpose This paper aims to answer the question of how the Polish representatives of social communication and media sciences communicate the most recent scientific findings in the media space, i.e. what types of publications are shared, what activities do they exemplify (sharing information about their own publications, leading discussions, formulating opinions), what is the form of the scientific communication created by them (publication of reference lists' descriptions, full papers, preprints and post prints) and what is the audience reception (number of downloads, displays, comments). Design/methodology/approach The authors present the results of analysis conducted on the presence of the most recent (2017–2019) publications by the Polish representatives of the widely understood social communication and media sciences in three selected social networking services for scientists: ResearchGate, Google Scholar and Academia.edu. The analyses covered 100 selected representatives of the scientific environment (selected in interval sampling), assigned, according to the OECD classification “Field of Science”, in the “Ludzie nauki” (Men of Science) database to the “media and communication” discipline. Findings The conducted analyses prove a low usage level of the potential of three analysed services for scientists by the Polish representatives of social communication and media sciences. Although 60% of them feature profiles in at least one of the services, the rest are not present there at all. From the total of 113 identified scientists' profiles, as little as 65 feature publications from 2017 to 2019. Small number of alternative metrics established in them, implies, in turn, that if these metrics were to play an important role in evaluation of the value and influence of scientific publications, then this evaluation for the researched Polish representatives of social communication and media sciences would be unfavourable. Originality/value The small presence of the Polish representatives of the communication and media sciences in three analysed services shows that these services may be – for the time being – only support the processes of managing own scientific output. Maybe this quite a pessimistic image of scientists' activities in the analysed services is conditioned by a simple lack of the need to be present in electronic channels of scientific communication or the lack of trust to the analysed services, which, in turn, should be linked to their shortcomings and flaws. However, unequivocal confirmation of these hypotheses might be brought by explorations covering a larger group of scientists, and complemented with survey studies. Thus, this research may constitute merely a starting point for further explorations, including elaboration of good practices with respect to usage of social media by scientists.


2015 ◽  
Vol 67 (1) ◽  
pp. 94-115 ◽  
Author(s):  
David Haynes ◽  
Lyn Robinson

Purpose – The purpose of this paper is to identify the risks faced by users of online social networking services (SNSs) in the UK and to develop a typology of risk that can be used to assess regulatory effectiveness. Design/methodology/approach – An initial investigation of the literature revealed no detailed taxonomies of risk in this area. Existing taxonomies were reviewed and merged with categories identified in a pilot survey and expanded in purposive sample survey directed at the library and information services (LIS) community in the UK. Findings – Analysis of the relationships between different risk categories yielded a grouping of risks by their consequences. This aligns with one of the objectives of regulation, which is to mitigate risks. Research limitations/implications – This research offers a tool for evaluation of different modes of regulation of social media. Practical implications – Awareness of the risks associated with use of online SNSs and wider social media contributes to the work of LIS professionals in their roles as: educators; intermediaries; and users of social media. An understanding of risk also informs the work of policy makers and legislators responsible for regulating access to personal data. Originality/value – A risk-based view of regulation of personal data on social media has not been attempted in such a comprehensive way before.


2014 ◽  
Vol 29 (2) ◽  
pp. 188-205 ◽  
Author(s):  
Te-Lin Chung ◽  
Sara Marcketti ◽  
Ann Marie Fiore

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