CloseUp—A Community-Driven Live Online Search Engine

2019 ◽  
Vol 19 (3) ◽  
pp. 1-21
Author(s):  
Christian Von Der Weth ◽  
Ashraf Abdul ◽  
Abhinav R. Kashyap ◽  
Mohan S. Kankanhalli
Keyword(s):  
Search Engine ◽  
Online Search

Forecasting Tourism Demand using Text Mining Techniques: Focused on an Online Search Engine

2017 ◽  
Vol 41 (1) ◽  
pp. 13-27
Author(s):  
Su-Ji Park ◽  
Jin-Ok Shin ◽  
Sang-Hun Song ◽  
Chul Jeong
Keyword(s):  
Text Mining ◽  
Search Engine ◽  
Tourism Demand ◽  
Online Search

scholarly journals An exploration into the information-seeking behaviours of engineers and scientists

2017 ◽  
Vol 51 (3) ◽  
pp. 789-800 ◽  
Author(s):  
Susan Wellings ◽  
Biddy Casselden
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Information Seeking ◽  
Mixed Methods Research ◽  
Small Sample Size ◽  
Small Sample ◽  
Online Search ◽  
Online Questionnaire ◽  
Engine Operation ◽  
The Uk

This article considers findings from Master’s research that investigated the information-seeking behaviours of engineers and scientists in the workplace. The objectives of this research were to establish where engineers and scientists look for information, consider their search preferences and determine the understanding they have of online search engine operation. There is limited current research in these areas looking at engineers and scientists in the workplace. The research was undertaken using a mixed methods research methodology. A survey was conducted with engineers and scientists working in the UK, using an online questionnaire and interviews to obtain quantitative and qualitative data. Due to the small sample size (115: 58 engineers, 57 scientists) this research does not make generalisations about the wider population. The research showed both similarities and differences between engineers’ and scientists’ information-seeking behaviours. The most popular resources used by both engineers and scientists were online search engines, specialist databases and scholar search engines; and the most used sources were from within their own organisation (colleagues and documents). Electronic versions of sources were preferred over print because of their searchability; however, when an item was found it was often printed out to read. Although the main focus of this research was not information literacy it is suggested that there are significant gaps in the understanding of search engine functionality by both engineers and scientists, even though it is the most heavily used resource for information seeking. Whilst this research does not make generalisations about the wider engineer and scientist populations, potential implications for information professionals working with these groups are considered.

Airing Grievances Online: Search Engine Algorithms and the Fate of Minorities at Risk

2008 ◽  
Vol 4 (3) ◽  
pp. 3-17 ◽  
Author(s):  
Victor Asal ◽  
Paul G. Harwood
Keyword(s):  
At Risk ◽  
Search Engine ◽  
Online Search ◽  
Minorities At Risk

Credible to Whom?

2017 ◽  
pp. 142-161
Author(s):  
Nathan Rodriguez
Keyword(s):  
Public Health ◽  
Social Media ◽  
Search Engine ◽  
Online Search ◽  
Case Study Approach ◽  
Study Approach ◽  
Active Choice ◽  
Echo Chamber ◽  
Chamber Effect

This chapter adopts a case study approach to examine the echo chamber effect online. Individuals cobble together personalized newsfeeds by active choice and those choices are often accompanied by subtle manipulations in social media and online search engine algorithms that may shape and constrain the parameters of information on a given topic. In this chapter, the author studied vaccine-hesitant discourse in an online forum over a five-year period. Those conversations exhibited characteristics of what would be considered an echo chamber, as defined by Jamieson and Cappella (2008). The implications of this case study suggest that the echo chamber within the realm of vaccination can lead individuals toward content and information of dubious veracity, with significant implications for public health.

Google Scholar's Filter Bubble

2017 ◽  
pp. 211-229
Author(s):  
Ke Yu ◽  
Nazeem Mustapha ◽  
Nadeem Oozeer
Keyword(s):  
Social Science ◽  
Search Engine ◽  
Google Scholar ◽  
Online Search ◽  
Search Behaviour ◽  
Search Results ◽  
Search Terms ◽  
Exploratory Experiment ◽  
Filter Bubble ◽  
Academic Search

This chapter investigates the allegation that popular online search engine Google applies algorithms to personalise search results therefore yielding different results for the exact same search terms. It specifically examines whether the same alleged filter bubble applies to Google's academic product: Google Scholar. It reports the results from an exploratory experiment of nine keywords carried out for this purpose, varying variables such as disciplines (Natural Science, Social Science and Humanities), geographic locations (north/south), and levels (senior/junior researchers). It also reports a short survey on academic search behaviour. The finding suggests that while Google Scholar, together with Google, has emerged as THE dominant search engine among the participants of this study, the alleged filter bubble is only mildly observable. The Jaccard similarity of search results for all nine keywords is strikingly high, with only one keyword that exhibits a localized bubble at 95% level. This chapter therefore concludes that the filter bubble phenomenon does not warrant concern.

scholarly journals Distinct Diurnal and Day of Week Online Search Patterns Related to Common Eye Conditions

2020 ◽  
Author(s):  
Michael S. Deiner ◽  
Stephen D. McLeod ◽  
Julie M. Schallhorn ◽  
James Chodosh ◽  
Daniel H. Hwang ◽  
...  
Keyword(s):  
Search Engine ◽  
Time Of Day ◽  
Online Search ◽  
Eye Care ◽  
Cyclic Patterns ◽  
Diurnal Patterns ◽  
Search Terms ◽  
Eye Health ◽  
Search Patterns ◽  
Search Data

AbstractImportanceStudies suggest diurnal patterns of some eye conditions. Leveraging new information sources such as online search data to learn more about such patterns could improve understanding of patient eye-related conditions and well-being and improve timing of clinical and remote eye care.ObjectiveTo investigate our hypothesis that the public is likely to consistently search about different eye conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to eye conditions such as conjunctivitis. We asked if search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other.DesignHourly search data for eye-related and control search terms for 2018 were analyzed and compared.SettingData from 10 USA states.ExposureInternet search.ParticipantsPopulations that searched Google’s search engine using our chosen study terms.Main Outcome MeasuresCyclical hourly and weekly online search patterns.ResultsDistinct diurnal (p<0.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented reported clinical patterns. Of the eye related terms, “conjunctivitis” and “pink eye” had the strongest diurnal cyclic patterns based on peak-to-trough ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. In contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening to morning period and peaking in early morning.Conclusions and RelevanceThe frequency of online searches for various eye conditions can show cyclic patterns according to time of day or week. Further studies to understand the reasons for these variations may help supplement current clinical understanding of eye symptom presentation and improve the timeliness of patient messaging and care interventions.Key PointsQuestionDo online public search engine queries for different eye-health terms follow hourly or daily patterns and do the patterns differ from each other or reflect what is known clinically?FindingsUnique hourly and day of week eye health related search patterns appear diurnal and can reflect what has been observed clinically.MeaningOnline search data may reflect timing of eye conditions and could improve clinical understanding of eye-related symptom occurrence, including outside of clinics. Knowing precisely when patient’s eye condition interests increase holds promise -for example to optimize timing and availability of local or remote eye care resources.

scholarly journals Cluster anxiety-related adverse events following immunization (AEFI): An assessment of reports detected in social media and those identified using an online search engine

Vaccine ◽  
2018 ◽  
Vol 36 (40) ◽  
pp. 5949-5954 ◽  
Author(s):  
Tiffany A. Suragh ◽  
Smaragda Lamprianou ◽  
Noni E. MacDonald ◽  
Anagha R. Loharikar ◽  
Madhava R. Balakrishnan ◽  
...  
Keyword(s):  
Social Media ◽  
Adverse Events ◽  
Search Engine ◽  
Online Search

ECanon: online search engine for canonical texts

2004 ◽  
Vol 41 (12) ◽  
pp. 41Sup-0192-41Sup-0192
Keyword(s):  
Search Engine ◽  
Online Search ◽  
Canonical Texts
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