search behaviors
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2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 660-660
Author(s):  
Matthew Picchiello ◽  
Payton Rule ◽  
Tina Lu ◽  
Brian Carpenter

Abstract Nearly 60% of older adults use the internet for health-related reasons. Some studies have demonstrated differences in the frequency at which men and women perform various online activities. However, few studies have investigated gender differences in health-related search behaviors (HRSB). The purpose of this study was to examine differences in self-reported HRSB between older men and women. A total of 47 older adults (M age = 66.6, 55% female, 87% White) completed a survey assessing perceived usefulness and trust in the internet for health-care information, types of websites used, and reasons for looking up health information. Independent samples t-tests revealed that, compared to women, men regard the internet as more useful in helping them make health care decisions (t (45) = 2.715) and as a more trustworthy source (t (45) = 2.24, p's < 0.05). Men were more likely to get health information through sources affiliated with educational institutions (χ2(1) = 3.9) and government agencies (χ2(1) = 8.8), whereas women were more likely to use social media, (χ2(1) = 4.3, p's < 0.05). Lastly, men were more likely to use the internet to learn about information on medical procedures (χ2(1) = 5.1), while women were more likely to learn about alternative treatments (χ2(1) = 4.9, p 's < 0.05) online. As 72.3% of participants indicated the internet as their first source for health information, interventions geared towards enhancing HRSB for older adults are needed, especially for older women whose HRSB may make them particularly vulnerable to misinformation.


SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110672
Author(s):  
Ruirui Lian ◽  
Wenjing Cai ◽  
Kun Chen ◽  
Hongru Shen ◽  
Xiaopei Gao ◽  
...  

The present research aims to explore the impact of mentoring relationship on college graduates’ job search behavior among Chinese undergraduate students by examining the mediator of job search intention and the moderator of job search self-efficacy. A two-wave survey study was conducted in China ( N = 594). Our findings show a positive indirect relation between mentoring and college graduates’ job search behaviors through job search intention. The graduates’ job search self-efficacy positively moderated the indirect relationship such that when job search self-efficacy was higher, the influence of mentoring on behavior via job search intention was stronger. These findings extend the literature by clarifying how and when mentoring facilitates graduates’ job search behaviors and provide practical implications for facilitating a smooth school-to-work transition in China. As the first study that empirically clarifies why (through job search intention) and when (job search self-efficacy) mentoring function is positively related to job search behavior among Chinese undergraduate students, the present study contributes to the existing mentoring and job search literature. Future research is encouraged to extend the findings by integrating theory of planned behavior (TPB) with self-regulation theory toward deepening current understanding of how and when mentoring can contribute to a student’s success in job search behavior.


Author(s):  
Luyan Xu ◽  
Xuan Zhou

AbstractEvaluation of interactive search systems and study of users’ struggling search behaviors require a significant number of search tasks. However, generation of such tasks is inherently difficult, as each task is supposed to trigger struggling search behavior rather than simple search behavior. To the best of our knowledge, there has not been a commonly used task set for research in struggling search. Moreover, the everchanging landscape of information needs would render old task sets less ideal if not unusable for evaluation. To deal with this problem, we propose a crowd-powered task generation method and develop a platform to efficiently generate struggling search tasks on basis of online wikis such as Wikipedia. Our experiments and analysis show that the generated tasks are qualified to emulate struggling search behaviors consisting of “repeated similar queries” and “quick-back clicks”; tasks of diverse topics, high quality and difficulty can be created using this method. For benefit of the community, we publicly released a task generation platform TaskGenie, a task set of 80 topically diverse struggling search tasks with “baselines,” and the corresponding anonymized user behavior logs.


2021 ◽  
Vol 13 (15) ◽  
pp. 8528
Author(s):  
Reem Alshahrani ◽  
Amal Babour

Infodemiology uses web-based data to inform public health policymakers. This study aimed to examine the diffusion of Arabic language discussions and analyze the nature of Internet search behaviors related to the global COVID-19 pandemic through two platforms (Twitter and Google Trends) in Saudi Arabia. A set of Twitter Arabic data related to COVID-19 was collected and analyzed. Using Google Trends, internet search behaviors related to the pandemic were explored. Health and risk perceptions and information related to the adoption of COVID-19 infodemic markers were investigated. Moreover, Google mobility data was used to assess the relationship between different community activities and the pandemic transmission rate. The same data was used to investigate how changes in mobility could predict new COVID-19 cases. The results show that the top COVID-19–related terms for misinformation on Twitter were folk remedies from low quality sources. The number of COVID-19 cases in different Saudi provinces has a strong negative correlation with COVID-19 search queries on Google Trends (Pearson r = −0.63) and a statistical significance (p < 0.05). The reduction of mobility is highly correlated with a decreased number of total cases in Saudi Arabia. Finally, the total cases are the most significant predictor of the new COVID-19 cases.


2021 ◽  
Vol 12 ◽  
Author(s):  
Xuejun Jin ◽  
Xue Zhou ◽  
Xiaolan Yang ◽  
Yiyang Lin

It is a well-documented phenomenon that individuals stop searching earlier than predicted by the optimal, risk-neutral stopping rule, leading to inefficient searches. Individuals' search behaviors during making investment decisions in financial markets can be easily affected by their peers. In this study, we designed a search game in a simplified experimental stock market in which subjects were required to search for the best sell prices for their stocks. By randomly assigning subjects into pairs and presenting them with real-time information on their peers' searches, we investigated the effects of peers' decisions on search behaviors. The results showed that two subjects in the same group with real-time peer information learned and engaged in similar search behaviors. However, this peer effect did not exist when subjects had access to feedback information on the ex-post best response. In addition, we found that the presence of information about peers' decisions alone had no significant impact on search efficiency, whereas access to both information on peers' decisions and feedback information significantly improved subjects' search efficiency.


2021 ◽  
Author(s):  
Zhenling Jiang ◽  
Tat Chan ◽  
Hai Che ◽  
Youwei Wang

This paper empirically investigates how marketers can retarget consumers who have searched online but did not purchase, based on their search behaviors.


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