The Experts below are selected from a list of 17310 Experts worldwide ranked by ideXlab platform
Mike M Nguyen - One of the best experts on this subject based on the ideXlab platform.
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Internet Search trends analysis tools can provide real time data on kidney stone disease in the united states
Urology, 2013Co-Authors: Scott D Willard, Mike M NguyenAbstract:Objectives To evaluate the utility of using Internet Search trends data to estimate kidney stone occurrence and understand the priorities of patients with kidney stones. Internet Search trends data represent a unique resource for monitoring population self-reported illness and health information-seeking behavior. Methods The Google Insights for Search analysis tool was used to study Searches related to kidney stones, with each Search term returning a Search volume index (SVI) according to the Search frequency relative to the total Search volume. SVIs for the term, "kidney stones," were compiled by location and time parameters and compared with the published weather and stone prevalence data. Linear regression analysis was performed to determine the association of the Search interest score with known epidemiologic variations in kidney stone disease, including latitude, temperature, season, and state. The frequency of the related Search terms was categorized by theme and qualitatively analyzed. Results The SVI correlated significantly with established kidney stone epidemiologic predictors. The SVI correlated with the state latitude (R-squared = 0.25; P P P P P = .003, respectively). The national SVI correlated strongly with the average U.S. temperature by month (R-squared = 0.54; P = .007). The Search term ranking suggested that Internet users are most interested in the diagnosis, followed by etiology, infections, and treatment. Conclusions Geographic and temporal variability in kidney stone disease appear to be accurately reflected in Internet Search trends data. Internet Search trends data might have broader applications for epidemiologic and urologic reSearch.
Tsaichin-chung - One of the best experts on this subject based on the ideXlab platform.
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Exploring the roles of education and Internet Search experience in students' Internet-specific epistemic beliefs
Computers in Human Behavior, 2016Co-Authors: Chiuyen-lin, Liangjyh-chong, Tsaichin-chungAbstract:The main purpose of this study was to explore the role of education and Internet Search experience in students' Internet-specific epistemic beliefs while Searching for course-related information on...
Chin-chung Tsai - One of the best experts on this subject based on the ideXlab platform.
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Exploring the roles of education and Internet Search experience in students' Internet-specific epistemic beliefs
Computers in Human Behavior, 2016Co-Authors: Yen-lin Chiu, Jyh-chong Liang, Chin-chung TsaiAbstract:The main purpose of this study was to explore the role of education and Internet Search experience in students' Internet-specific epistemic beliefs while Searching for course-related information on the Internet. The Chinese version of the Internet-Specific Epistemic Questionnaire (C-ISEQ) was utilized to evaluate participants' epistemic beliefs regarding the uncertainty, complicity, and source of Internet-based knowledge as well as the justification of Internet-based knowing. A total of 1070 students with educational levels ranging from junior high school to undergraduate were surveyed. Hierarchical regression analyses were conducted to examine the relationships of education and Internet Search experience with students' Internet-specific epistemic beliefs. In addition, the interaction effect between years of education and Internet Search experience was recruited in the regression model to explore its correlations with Internet-specific epistemic beliefs. The results showed that years of education were positively correlated to uncertainty and source of Internet-based knowledge as well as justification of Internet-based knowing. Also, Internet Search experience had negative relations with uncertainty, complexity and source of Internet-based knowledge; however, it was positively related to justification of Internet-based knowing. In addition, the interaction effect between years of education and Internet Search experience was significantly linked to justification of Internet-based knowing. The results of this study highlight the importance of education in students' development of Internet-specific epistemic beliefs. Implications for further reSearch and Internet-based instruction are discussed. Years of education positively affected Internet-specific epistemic beliefs.Internet Search experience increased justification of Internet-based knowing.Internet Search experience negatively impacted uncertainty, complexity and source.
Arash Sattari - One of the best experts on this subject based on the ideXlab platform.
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Correlating Refugee Border Crossings with Internet Search Data
2018 IEEE International Conference on Information Reuse and Integration (IRI), 2018Co-Authors: Panos Kostakos, Abhinay Pandya, Mourad Oussalah, Simo Hosio, Christoph Breidbach, Vassilis Kostakos, Niels Van Berkel, Olga Kyriakouli, Arash SattariAbstract:Can Internet Search data be used as a proxy to predict refugee mobility? The soaring refugee death toll in Europe creates an urgent need for novel tools that monitor and forecast refugee flows. This study investigates the correlation between refugee mobility data and Internet Search data from Google Trends. Google Trends is a freely accessible tool that provides access to Internet Search data by analyzing a sample of all web queries. In our study, we surveyed refugees in Greece (entry point) and in Finland (destination point) to identify what Search queries they had used during their travel. Next, we conducted time series analysis on Google Search data to investigate whether interest in user-defined Search queries correlated with the levels of refugee arrival data recorded by the United Nations High Commissioner for Refugees (UNHCR). Results indicate that the reuse of Internet Search data considerably improves the predictive power of the models.
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IRI - Correlating Refugee Border Crossings with Internet Search Data
2018 IEEE International Conference on Information Reuse and Integration (IRI), 2018Co-Authors: Panos Kostakos, Abhinay Pandya, Mourad Oussalah, Simo Hosio, Christoph Breidbach, Vassilis Kostakos, Niels Van Berkel, Olga Kyriakouli, Arash SattariAbstract:Can Internet Search data be used as a proxy to predict refugee mobility? The soaring refugee death toll in Europe creates an urgent need for novel tools that monitor and forecast refugee flows. This study investigates the correlation between refugee mobility data and Internet Search data from Google Trends. Google Trends is a freely accessible tool that provides access to Internet Search data by analyzing a sample of all web queries. In our study, we surveyed refugees in Greece (entry point) and in Finland (destination point) to identify what Search queries they had used during their travel. Next, we conducted time series analysis on Google Search data to investigate whether interest in user-defined Search queries correlated with the levels of refugee arrival data recorded by the United Nations High Commissioner for Refugees (UNHCR). Results indicate that the reuse of Internet Search data considerably improves the predictive power of the models.
Scott D Willard - One of the best experts on this subject based on the ideXlab platform.
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Internet Search trends analysis tools can provide real time data on kidney stone disease in the united states
Urology, 2013Co-Authors: Scott D Willard, Mike M NguyenAbstract:Objectives To evaluate the utility of using Internet Search trends data to estimate kidney stone occurrence and understand the priorities of patients with kidney stones. Internet Search trends data represent a unique resource for monitoring population self-reported illness and health information-seeking behavior. Methods The Google Insights for Search analysis tool was used to study Searches related to kidney stones, with each Search term returning a Search volume index (SVI) according to the Search frequency relative to the total Search volume. SVIs for the term, "kidney stones," were compiled by location and time parameters and compared with the published weather and stone prevalence data. Linear regression analysis was performed to determine the association of the Search interest score with known epidemiologic variations in kidney stone disease, including latitude, temperature, season, and state. The frequency of the related Search terms was categorized by theme and qualitatively analyzed. Results The SVI correlated significantly with established kidney stone epidemiologic predictors. The SVI correlated with the state latitude (R-squared = 0.25; P P P P P = .003, respectively). The national SVI correlated strongly with the average U.S. temperature by month (R-squared = 0.54; P = .007). The Search term ranking suggested that Internet users are most interested in the diagnosis, followed by etiology, infections, and treatment. Conclusions Geographic and temporal variability in kidney stone disease appear to be accurately reflected in Internet Search trends data. Internet Search trends data might have broader applications for epidemiologic and urologic reSearch.
