Relevant bibliographies by topics / Users’ behaviors

Academic literature on the topic 'Users’ behaviors'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Users’ behaviors"

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Chin, Chih-Yu, Hsi-Peng Lu, and Chao-Ming Wu. "Facebook Users' Motivation for Clicking the “Like” Button." Social Behavior and Personality: an international journal 43, no. 4 (May 24, 2015): 579–92. http://dx.doi.org/10.2224/sbp.2015.43.4.579.

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To explore the motivation and behavior of Facebook users when clicking the “Like” button, we analyzed the behaviors of 743 university student Facebook users using motivational theory and the theory of reasoned action. The main study findings were as follows: (a) hedonic motivation, utilitarian motivation, compliance motivation, conformity motivation, and affiliation motivation all had a positive impact on attitudes toward “Like”-clicking behaviors; (b) subjective norms and attitudes toward “Like”-clicking behaviors all had a positive impact on behavioral intention, and (c) behavioral intention had a positive impact on actual behaviors. These findings provide a valuable basis for constructing an explanatory model for “Like”-clicking behaviors of Facebook community platform users, as well as making significant practical contributions to enhance social and commercial benefits for businesses and individuals.
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Xu, Bing, Zhijun Ding, and Hongzhong Chen. "Recommending Locations Based on Users’ Periodic Behaviors." Mobile Information Systems 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/7871502.

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The research of location recommendation system is an important topic in the field of LBSN (Location-Based Social Network). Recently, more and more researchers began focusing on researching how to recommend locations based on user’s life behavior. In this paper, we proposed a new model recommending locations based on user’s periodic behaviors. In view of multiple periodic behaviors existing in time series, an algorithm which can mine all periods in time series is proposed in this paper. Based on the periodic behaviors, we recommend locations using item-based collaborative filtering algorithm. In this paper, we will also introduce our recommendation system which can collect users’ GPS trajectory, mine user’s multiple periods, and recommend locations based user’s periodic behavior.
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Boqing Feng, Boqing Feng, Mohan Liu Boqing Feng, and Jiuqiang Jin Mohan Liu. "Density Space Clustering Algorithm Based on Users Behaviors." 電腦學刊 33, no. 2 (April 2022): 201–9. http://dx.doi.org/10.53106/199115992022043302018.

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<p>At present, insider threat detection requires a series of complex projects, and has certain limitations in practical applications; in order to reduce the complexity of the model, most studies ignore the timing of user behavior and fail to identify internal attacks that last for a period of time. In addition, companies usually categorize the behavior data generated by all users and store them in different databases. How to collaboratively process large-scale heterogeneous log files and extract characteristic data that accurately reflects user behavior is a difficult point in current research. In order to optimize the parameter selection of the DBSCAN algorithm, this paper proposes a Psychometric Data & Attack Threat Density Based Spatial Clustering of Applications with Noise algorithm (PD&AT-DBSCAN). This algorithm can improve the accuracy of clustering results. The simulation results show that this algorithm is better than the traditional DBSCAN algorithm in terms of Rand index and normalized mutual information.</p> <p>&nbsp;</p>
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Boqing Feng, Boqing Feng, Mohan Liu Boqing Feng, and Jiuqiang Jin Mohan Liu. "Density Space Clustering Algorithm Based on Users Behaviors." 電腦學刊 33, no. 2 (April 2022): 201–9. http://dx.doi.org/10.53106/199115992022043302018.

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<p>At present, insider threat detection requires a series of complex projects, and has certain limitations in practical applications; in order to reduce the complexity of the model, most studies ignore the timing of user behavior and fail to identify internal attacks that last for a period of time. In addition, companies usually categorize the behavior data generated by all users and store them in different databases. How to collaboratively process large-scale heterogeneous log files and extract characteristic data that accurately reflects user behavior is a difficult point in current research. In order to optimize the parameter selection of the DBSCAN algorithm, this paper proposes a Psychometric Data & Attack Threat Density Based Spatial Clustering of Applications with Noise algorithm (PD&AT-DBSCAN). This algorithm can improve the accuracy of clustering results. The simulation results show that this algorithm is better than the traditional DBSCAN algorithm in terms of Rand index and normalized mutual information.</p> <p>&nbsp;</p>
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Useche, Sergio A., Javier Gene-Morales, Felix W. Siebert, Francisco Alonso, and Luis Montoro. "“Not as Safe as I Believed”: Differences in Perceived and Self-Reported Cycling Behavior between Riders and Non-Riders." Sustainability 13, no. 4 (February 3, 2021): 1614. http://dx.doi.org/10.3390/su13041614.

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Cycling behavior remains a key issue for explaining several traffic causalities occurring every day. However, recent studies have shown how the assessment of the own safety-related behaviors on the road may substantially differ from how third parties assess them. Thus, the aim of this study was to evaluate the differences between cyclists’ self-reported behavior and the proxy-reported behavior that other (non-cyclist) road users perceive from bike riders. For this purpose, this study used data from two samples: (i) 1064 cyclists (M = 32.83 years) answering the Cycling Behavior Questionnaire—CBQ, and (ii) 1070 non-cyclists (M = 30.83 years) answering an adapted version of the CBQ for external raters—ECBQ. The results show how the self-reported and proxy-reported behaviors of cyclists greatly differ in terms of all behavioral factors composing the CBQ model, i.e., traffic violations, riding errors, and positive behaviors. Also, external raters (non-cyclists) are those targeting significantly riskier behaviors than those self-reported by cyclists. These discrepancies between perceived behaviors may give rise to conflicting viewpoints on the interaction between bicycle riders and other road users. Therefore, this study underscores the importance of behavioral awareness, providing highlights for future studies on the behavioral interaction between cyclists and other road users. Results can be used to improve the road safety of all road users by giving indications on self-and proxy-perceived safety-related behaviors and visibility of protective riding habits.
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Memon, Ambreen, Jeff Kilby, Jose Breñosa, Julio César Martínez Espinosa, and Imran Ashraf. "Analysis and Implementation of Human Mobility Behavior Using Similarity Analysis Based on Co-Occurrence Matrix." Sensors 22, no. 24 (December 15, 2022): 9898. http://dx.doi.org/10.3390/s22249898.

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The fast expansion of ICT (information and communications technology) has provided rich sources of data for the analysis, modeling, and interpretation of human mobility patterns. Many researchers have already introduced behavior-aware protocols for a better understanding of architecture and realistic modeling of behavioral characteristics, similarities, and aggregation of mobile users. We are introducing the similarity analytical framework for the mobile encountering analysis to allow for more direct integration between the physical world and cyber-based systems. In this research, we propose a method for finding the similarity behavior of users’ mobility patterns based on location and time. This research was conducted to develop a technique for producing co-occurrence matrices of users based on their similar behaviors to determine their encounters. Our approach, named SAA (similarity analysis approach), makes use of the device info i.e., IP (internet protocol) and MAC (media access control) address, providing an in-depth analysis of similarity behaviors on a daily basis. We analyzed the similarity distributions of users on different days of the week for different locations based on their real movements. The results show similar characteristics of users with common mobility behaviors based on location and time to showcase the efficacy. The results show that the proposed SAA approach is 33% more accurate in terms of recognizing the user’s similarity as compared to the existing similarity approach.
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Schmidt, Peter, Galit Gordoni, Icek Ajzen, Christoph Beuthner, Eldad Davidov, Henning Silber, Holger Steinmetz, and Bernd Weiß. "Twitter Users’ Privacy Behavior: A Reasoned Action Approach." Social Media + Society 8, no. 3 (July 2022): 205630512211260. http://dx.doi.org/10.1177/20563051221126085.

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Social networking sites have become a predominant means of communication across the globe. Activities on these sites generate massive amounts of personal information and raise concerns about its potential abuse. Means designed to protect the user’s privacy and prevent exploitation of confidential data often go unused. In this study, we draw on the theory of planned behavior, a reasoned action approach, to explain intentions to adopt privacy behaviors on social networking sites, with a focus on Twitter users. Consistent with the theory, an online survey of Twitter users ( n = 1,060) found that instrumental and experiential attitudes and descriptive and injunctive subjective norms regarding these behaviors were direct predictors of intentions. Perceived behavioral control had a moderating effect, such that subjective norm was a better predictor of intentions for participants high as opposed to low in perceived control. We briefly discuss the implications of these results for developing theory-driven and evidence-based interventions to promote privacy behavior.
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Herrera, Gail. "Google Scholar Users and User Behaviors: An Exploratory Study." College & Research Libraries 72, no. 4 (July 1, 2011): 316–30. http://dx.doi.org/10.5860/crl-125rl.

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The University of Mississippi Library created a profile to provide linking from Google Scholar (GS) to library resources in 2005. Although Google Scholar does not provide usage statistics for institutions, use of Google Scholar is clearly evident in looking at library link resolver logs. The purpose of this project is to examine users of Google Scholar with existing data from interlibrary loan transactions and library Web site click-through logs and analytics. Questions about user status and discipline, as well as behaviors related to use of other library resources, are explored.
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Miller, Kathleen E., Grace M. Barnes, Don Sabo, Merrill J. Melnick, and Michael P. Farrell. "A Comparison of Health Risk Behavior in Adolescent Users of Anabolic-Androgenic Steroids, by Gender and Athlete Status." Sociology of Sport Journal 19, no. 4 (December 2002): 385–402. http://dx.doi.org/10.1123/ssj.19.4.385.

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Contrary to popular assumption, adolescent anabolic-androgenic steroid use is not limited to serious male athletes. This paper examines the relationships among gender, athletic participation, and health-related problem behaviors among adolescent steroid users. Regression analyses were performed on a nationally representative sample of over 16,000 high school students (the 1997 Youth Risk Behavior Survey), of whom nearly 500 had used steroids. Compared to nonusers, steroid users were significantly more likely to report substance use, suicidal behavior, and sexual risk-taking; however, patterns of risk behavior varied by the user’s athletic status and gender. After controlling for age, race, ethnicity, and parental education, both athletic participation and female gender were negatively associated with most risk behaviors among users of anabolic steroids.
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Mu, Xiaodong, Zhaoju Zeng, Danyao Shen, and Bo Zhang. "Multi-Feature Behavior Relationship for Multi-Behavior Recommendation." Applied Sciences 12, no. 24 (December 15, 2022): 12909. http://dx.doi.org/10.3390/app122412909.

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Multi-behavior recommendation aims to model the interaction information of multiple behaviors to enhance the target behavior’s recommendation performance. Despite progress in recent research, it is challenging to represent users’ preferences using the multi-feature behavior information of user interactions. In this paper, we propose a Multi-Feature Behavior Relationship for Multi-Behavior Recommendation (MFBR) framework, which models the multi-behavior recommendation problem from both sequence structure and graph structure perspectives for user preference prediction of target behaviors. Specifically, the MFBR model is designed with a sequence encoder and a graph encoder to construct behavioral representations of different aspects of the user; the correlations between behaviors are modeled by a behavioral relationship encoding layer, and the importance of different behaviors is finally learned in order to construct the final representation of user preferences. Experimental validation conducted on two real-world recommendation datasets shows that our MFBR consistently outperforms state-of-the-art methods.
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Dissertations / Theses on the topic "Users’ behaviors"

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Noe, Heeju. "Fashion Renting: An Exploratory Study of Users and Non-users Behaviors." Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1628301642984733.

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Blount, Charles Lenward. "Users' privacy and security behaviors on mobile devices." Thesis, University of Maryland, Baltimore County, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1571723.

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Preferences and behaviors for privacy management with mobile applications are difficult to capture. Previous measures are mostly based on self-report data, which often does not accurately predict actual user behavior. A deeper understanding was sought, gleaned from observing actual practices. This thesis analyzes 11,777 applications from the Google Play marketplace in order to determine the impact of privacy settings on purchase behavior. This was done by looking at the effect of the number of privacy concessions as well as the effect of individual concessions and category on number of downloads. It was found that users of paid applications do not have a preference for fewer privacy concessions. This study further reinforces the disconnect between the user's often stated preference for privacy and their actual behavior -- a discrepancy known as the “privacy paradox ”. Theoretical and practical implications are discussed.

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Lee, Jesse Han-Leng. "Identifying users' information needs: A case of SIDC library." School of Communication & Information, Nanyang Technological University, 2006. http://hdl.handle.net/10150/105258.

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The Securities Industry Development Centre (SIDC) is the education and training arm of the Securities Commission (SC), and the SIDC Library serves both SC staff and the securities industry. The SIDC Library is a specialised library that has its resources focused on the capital market. Identifying usersâ information needs is a first step towards analysing the information needs of SIDC Library members and the SC staff. The study was motivated by the fact that an analysis of information needs help identify the SIDC Library resources for further development to ensure the delivery of information services matches usersâ needs. In this paper, we would like to share a study that was conducted to analyse how the SIDC Library services were tailored to meet the information needs of users. By studying this aspect, we will be able to see how the library defines and classifies its user types, and addresses issues impacting information services through proper operation planning and practices. The respondents for this paper were mainly SIDC Library members and SC staff. The result of the study is based on a collection of survey questionnaires, personal interviews and records of user requests for documents. From this study, a profile of user information needs was established; enabling the library management to identify, support and provide an efficient delivery mechanism for meeting usersâ information needs. This study helped SIDC librarians identify the kind of information that was needed and generated, and to support those which are not readily available by further developing a comprehensive new subject/collection of SIDC Library information resources. This will also provide an insight into the users' expectations on content resources and services of the SIDC Library, as well as for developing library user education programmes. Thus, the study of usersâ information needs is one tool that enables SIDC Librarians to discover, evaluate, implement, maintain and improve its management of information resources.
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McMillan, Tyson DeShaun. "Web Information Behaviors of Users Interacting with a Metadata Navigator." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc407784/.

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The web information behaviors of users as they interacted with a metadata navigator, the Personal Information (PI) Agent, and reflected upon their interaction experiences were studied. The process included studying the complete iterative (repeated) cycle of information needs, information seeking, and information use of users interacting with an internet-based prototype metadata PI Agent tool. Detlor’s theory of web information behaviors of organizational users was utilized as a theoretical foundation for studying human-information interactions via the PI Agent tool. The qualitative research design allowed for the use of triangulation within the context of a one-group pretest-posttest design. Triangulation occurred in three phases: (a) observe, (b) collect, and (c) reflect. Observations were made as participants solved three problem situations. Participants’ computer log and print screen data were collected, and follow-up interviews were conducted once all posttest sessions ended to enable users to reflect on their experiences. The three triangulation phases ensured saturation of data and greater depth regarding the participants’ information behaviors. Content analysis occurred via exploratory pattern analysis using the posttest Problem Steps Recorder (PSR) log data and on the six interviewees’ follow-up interview data. Users engaged in iterative cycles of information needs, information seeking, and information use to resolve the presented problem situations. The participants utilized the PI Agent tool iteratively to eliminate their knowledge gaps regarding the presented problem situations. This study was the first to use PSR log data for capturing evidence of the iterative search process as defined by Detlor. The implications for best practices were inspired by participant feedback, and recommendations for further study are made.
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Xiao, Guang Yi. "Personalized scheduling search advertisement by mining the history behaviors of users." Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2119532.

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Hashem, Yassir. "Multi-Modal Insider Threat Detection and Prevention based on Users' Behaviors." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc1248460/.

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Insider threat is one of the greatest concerns for information security that could cause more significant financial losses and damages than any other attack. However, implementing an efficient detection system is a very challenging task. It has long been recognized that solutions to insider threats are mainly user-centric and several psychological and psychosocial models have been proposed. A user's psychophysiological behavior measures can provide an excellent source of information for detecting user's malicious behaviors and mitigating insider threats. In this dissertation, we propose a multi-modal framework based on the user's psychophysiological measures and computer-based behaviors to distinguish between a user's behaviors during regular activities versus malicious activities. We utilize several psychophysiological measures such as electroencephalogram (EEG), electrocardiogram (ECG), and eye movement and pupil behaviors along with the computer-based behaviors such as the mouse movement dynamics, and keystrokes dynamics to build our framework for detecting malicious insiders. We conduct human subject experiments to capture the psychophysiological measures and the computer-based behaviors for a group of participants while performing several computer-based activities in different scenarios. We analyze the behavioral measures, extract useful features, and evaluate their capability in detecting insider threats. We investigate each measure separately, then we use data fusion techniques to build two modules and a comprehensive multi-modal framework. The first module combines the synchronized EEG and ECG psychophysiological measures, and the second module combines the eye movement and pupil behaviors with the computer-based behaviors to detect the malicious insiders. The multi-modal framework utilizes all the measures and behaviors in one model to achieve better detection accuracy. Our findings demonstrate that psychophysiological measures can reveal valuable knowledge about a user's malicious intent and can be used as an effective indicator in designing insider threat monitoring and detection frameworks. Our work lays out the necessary foundation to establish a new generation of insider threat detection and mitigation mechanisms that are based on a user's involuntary behaviors, such as psychophysiological measures, and learn from the real-time data to determine whether a user is malicious.
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White, Mel. "Information Seeking Behaviors in a Population of Assistive Mobility Device Users." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc799517/.

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The author explores the current state of information exchange and access in the procurement process for mobility assistive equipment. While the idealized model is of a linear process starting with a need and ending with the purchase, in practice the procedures for acquiring a device such as a wheelchair or electric scooter can be a time consuming task that involves client, family, medical care specialists, vendors, manufacturers, insurance companies and possibly alternate sources of funding. This study utilized Participatory Action Research (PAR) to collect both qualitative and quantitative data about information sources such as the Internet, the medical community, and vendors. The findings of this study suggest that in spite of the presence of the Internet, overall primary sources are similar to the traditional model and that for most there is no one source that could be easily accessed for information. A brief examination is made of the “Information landscape” utilized in the process and a brief discussion of two relatively unmentioned information sources: expos and the wheelchair sports community.
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Seymour, Zakiya Ayo-Zahra. "Understanding what sanitation users value - examining preferences and behaviors for sanitation systems." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52168.

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Over the last two decades, sanitation policy and development has undergone a paradigm shift away from heavily-subsidized, supply-driven approaches towards behavioral-based demand-driven approaches. These current approaches to increase sanitation demand are multi-faceted, requiring multiple stakeholders with varying degrees of interest, knowledge, and capacity. Although efforts exist to increase sanitation access by incorporating engineering design principles with implementation planning approaches, these groups generally work independently without strong connections, thus reducing the potential of their impact. As a result, the design of appropriate sanitation technology is disengaged from the implementation of acceptable technology into communities, disconnecting user preference integration from sanitation technology design and resulting in fewer sanitation technologies being adopted and used. To address these challenges in developing successful interventions, this research examined how user preferences for specific attributes of appropriate sanitation technologies and their respective implementation arrangements influence their adoption and usage. Data for the study included interviews of 1002 sanitation users living in a peri-urban area of South Africa; the surveyed respondents were asked about their existing sanitation technology, their preferences for various sanitation technology design attributes, as well as their perspectives on current and preferred sanitation implementation arrangements. The data revealed that user acceptability of appropriate sanitation technology is influenced by the adoption classification of the users. Through the identification of motives and barriers to sanitation usage that were statistically significant, it exhibited the need to differentiate users who share private sanitation from those use communal sanitation facilities. Results also indicated that user acceptability of appropriate sanitation systems is dependent on the technical design attributes of sanitation. The development of utility functions detailed the significance of seven technical design attributes and determined their respective priorities. An agent-based simulation examined how user preferences for sanitation technology design and implementation influence its adoption and usage. Findings suggest that user acceptability of sanitation technology is dependent on both the technology design and the implementation arrangement being preferred.
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Hashem, Yassir. "A Multi-Modal Insider Threat Detection and Prevention based on Users' Behaviors." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1248460/.

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Insider threat is one of the greatest concerns for information security that could cause more significant financial losses and damages than any other attack. However, implementing an efficient detection system is a very challenging task. It has long been recognized that solutions to insider threats are mainly user-centric and several psychological and psychosocial models have been proposed. A user's psychophysiological behavior measures can provide an excellent source of information for detecting user's malicious behaviors and mitigating insider threats. In this dissertation, we propose a multi-modal framework based on the user's psychophysiological measures and computer-based behaviors to distinguish between a user's behaviors during regular activities versus malicious activities. We utilize several psychophysiological measures such as electroencephalogram (EEG), electrocardiogram (ECG), and eye movement and pupil behaviors along with the computer-based behaviors such as the mouse movement dynamics, and keystrokes dynamics to build our framework for detecting malicious insiders. We conduct human subject experiments to capture the psychophysiological measures and the computer-based behaviors for a group of participants while performing several computer-based activities in different scenarios. We analyze the behavioral measures, extract useful features, and evaluate their capability in detecting insider threats. We investigate each measure separately, then we use data fusion techniques to build two modules and a comprehensive multi-modal framework. The first module combines the synchronized EEG and ECG psychophysiological measures, and the second module combines the eye movement and pupil behaviors with the computer-based behaviors to detect the malicious insiders. The multi-modal framework utilizes all the measures and behaviors in one model to achieve better detection accuracy. Our findings demonstrate that psychophysiological measures can reveal valuable knowledge about a user's malicious intent and can be used as an effective indicator in designing insider threat monitoring and detection frameworks. Our work lays out the necessary foundation to establish a new generation of insider threat detection and mitigation mechanisms that are based on a user's involuntary behaviors, such as psychophysiological measures, and learn from the real-time data to determine whether a user is malicious.
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Zhang, Guili. "HIV infection and risk behaviors among methamphetamine-dependent drug users in northern California /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2005. http://uclibs.org/PID/11984.

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Books on the topic "Users’ behaviors"

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Jana, Varlejs, and Rutgers University. School of Communication, Information, and Library Studies., eds. Information seeking: Basing services on users' behaviors. Jefferson, N.C: McFarland, 1987.

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Hall, Troy Elizabeth. Changes in the motivations, perceptions, and behaviors of recreation users: Displacement and coping in wilderness. Fort Collins, CO]: U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, 2007.

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Zhussupov, B. Study of behaviors associated with HIV infection, STI, and viral hepatitis among injecting drug users in Temirtau and Karaganda, Republic of Kazakhstan. Almaty [Kazakhstan]: CDC/Central Asia Office, 2007.

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Kowal, James A. Behavior models: Specifying users' expectations. Englewood Cliffs, New Jersey: Prentice-Hall, 1992.

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Kowal, James A. Behavior models: Specifying user's expectations. Englewood Cliffs, N.J: Prentice Hall, 1992.

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Verbeek, Peter-Paul, and Adriaan Slob, eds. User Behavior and Technology Development. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/978-1-4020-5196-8.

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School social behavior scales user's guide. 2nd ed. Baltimore: Paul H. Brookes Pub., 2008.

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Pemberton, James. Charitable behaviour. Reading, England: University of Reading, Dept. of Economics, 1995.

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McElrath, Karen. Drug use and risk behaviours among injecting drug users. Belfast: Drug & Alcohol Information Research Unit, Department of Health, Social Services and Public Safety, 2005.

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Hartgers, Christina. HIV risk behavior among injecting drug users in Amsterdam. Amsterdam: Rodopi, 1992.

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Book chapters on the topic "Users’ behaviors"

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Mathis, Diane A., Helen A. Navaline, David S. Metzger, and Jerome J. Platt. "Service Needs of Injection Drug Users." In Addictive Behaviors in Women, 329–58. Totowa, NJ: Humana Press, 1994. http://dx.doi.org/10.1007/978-1-4612-0299-8_13.

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Wilkinson, D. Adrian, and Simonne Lebreton. "Early Indications of Treatment Outcome in Multiple Drug Users." In Treating Addictive Behaviors, 239–61. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2191-0_11.

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Zhao, Guoshuai, Xueming Qian, and He Feng. "Personalized Recommendation by Exploring Social Users’ Behaviors." In MultiMedia Modeling, 181–91. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04117-9_17.

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Lin, Weijane, Hui-Chun Lin, and Hsiu-Ping Yueh. "Explore Elder Users’ Reading Behaviors with Online Newspaper." In Cross-Cultural Design, 184–92. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07308-8_18.

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He, Tieke, Hongzhi Yin, Zhenyu Chen, Xiaofang Zhou, and Bin Luo. "Predicting Users’ Purchasing Behaviors Using Their Browsing History." In Lecture Notes in Computer Science, 129–41. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19548-3_11.

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Li, Jiao, Kaige Zhu, and Juhyeok Jang. "Factors Influencing Users’ Content Sharing Intention in Travel-Related Consumer Generated Media." In Information and Communication Technologies in Tourism 2023, 113–27. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25752-0_13.

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AbstractTravel-related consumer generated media (CGM) plays an increasingly important role in travelers’ decision-making process. Strenuous effort has been dedicated to explore CGM’s impact on users’ travel behaviors. However, little is known about the motivations that drive users to post information on travel-related CGM. By combining the technology acceptance model (TAM), theory of planned behavior (TPB), and uses and gratifications theory (U&G), this study aims to delve into such motivational factors. The results revealed that users’ perceived ease of use when posting content significantly affects perceived usefulness. Additionally, users’ gratification derived from entertainment, information sharing, and rewards could positively influence their attitudes toward content sharing. Moreover, attitude, subjective norms, perceived behavioral control, and perceived usefulness jointly determine users’ intention to use travel-related CGM for content sharing. However, the impacts of perceived usefulness, perceived ease of use, status-seeking, socializing, and passing time on their attitudes toward content sharing were insignificant. This study tests the possibility of combining the TAM, TPB, and U&G to expand their application in the field of travel-related CGM, and provides suggestions for travel-related CGM managers to improve their services.
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Hausawi, Yasser M. "Current Trend of End-Users’ Behaviors Towards Security Mechanisms." In Lecture Notes in Computer Science, 140–51. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39381-0_13.

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Yan, Fei, Ming Zhang, Jian Tang, Tao Sun, Zhihong Deng, and Long Xiao. "Users’ Book-Loan Behaviors Analysis and Knowledge Dependency Mining." In Web-Age Information Management, 206–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14246-8_22.

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Kocielnik, Rafal, Gary Hsieh, and Daniel Avrahami. "Helping Users Reflect on Their Own Health-Related Behaviors." In Human–Computer Interaction Series, 85–115. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95579-7_5.

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Chen, Yipeng, Hongyan Li, Jinbo Zhang, and Gaoshan Miao. "Inferring Social Roles of Mobile Users Based on Communication Behaviors." In Web-Age Information Management, 402–14. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39937-9_31.

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Conference papers on the topic "Users’ behaviors"

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Liu, Shenghua, Houdong Zheng, Huawei Shen, Xueqi Cheng, and Xiangwen Liao. "Learning Concise Representations of Users' Influences through Online Behaviors." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/327.

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Whereas it is well known that social network users influence each other, a fundamental problem in influence maximization, opinion formation and viral marketing is that users' influences are difficult to quantify. Previous work has directly defined an independent model parameter to capture the interpersonal influence between each pair of users. However, such models do not consider how influences depend on each other if they originate from the same user or if they act on the same user. To do so, these models need a parameter for each pair of users, which results in high-dimensional models becoming easily trapped into the overfitting problem. Given these problems, another way of defining the parameters is needed to consider the dependencies. Thus we propose a model that defines parameters for every user with a latent influence vector and a susceptibility vector. Such low-dimensional and distributed representations naturally cause the interpersonal influences involving the same user to be coupled with each other, thus reducing the model's complexity. Additionally, the model can easily consider the sentimental polarities of users' messages and how sentiment affects users' influences. In this study, we conduct extensive experiments on real Microblog data, showing that our model with distributed representations achieves better accuracy than the state-of-the-art and pair-wise models, and that learning influences on sentiments benefit performance.
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Warsono, Mr, Ms Sarmini, and Syarifah Hasanah. "Deviant Behaviors of Teenage Drug Users." In Social Sciences, Humanities and Economics Conference (SoSHEC 2017). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/soshec-17.2018.48.

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Gacem, A., N. Nadjar-Gauthier, E. Monacelli, T. Al-ani, and Y. Oussar. "Behavior Identification for Wheelchair Driver Using the Fuzzy C-Means Classification Method." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82874.

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This study deals with behavior identification of Electric-Powered Wheelchair (EPW) drivers. User’s actions on the joystick determine this behavior. We assume that a driver evaluation can be performed using reference behaviors which are determined a priori. This study was carried out with two valid populations. The first one includes eight experimented subjects. The second includes six novice subjects. We propose to implement the Fuzzy C-Means (FCM) classification to separate different behaviors. The FCM was applied on the experimented population in order to determine reference’s behaviors. This shows that there were basically two different behaviors. An evaluation is performed on novice users by comparing their behaviors with respect to the reference ones. The results show that this population has an erratic behavior during the learning phase. Subsequently, users converge to one of the identified reference behaviors. We also evaluated a subject who suffers from muscular dystrophy and uses an EPW in everyday life. The results show a steady driving behavior.
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Dostert, Maureen, and Diane Kelly. "Users' stopping behaviors and estimates of recall." In the 32nd international ACM SIGIR conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1571941.1572145.

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Chandramohan, Senthilkumar, Matthieu Geist, Fabrice Lefevre, and Olivier Pietquin. "Clustering behaviors of Spoken Dialogue Systems users." In ICASSP 2012 - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2012. http://dx.doi.org/10.1109/icassp.2012.6289038.

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Zhang, Xiangmin, Michael Cole, and Nicholas Belkin. "Predicting users' domain knowledge from search behaviors." In the 34th international ACM SIGIR conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2009916.2010131.

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Villamarín-Salomón, Ricardo Mark, and José Carlos Brustoloni. "Using reinforcement to strengthen users' secure behaviors." In the 28th international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1753326.1753382.

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Cella, Leonardo. "Modelling User Behaviors with Evolving Users and Catalogs of Evolving Items." In UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3099023.3102251.

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Yonezu, Soji, and Hirotaka Osawa. "Telepresence robot with behavior synchrony: Merging the emotions and behaviors of users." In 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, 2017. http://dx.doi.org/10.1109/roman.2017.8172304.

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Lee, Yue-Shi, Show-Jane Yen, and Chia-Hui Wang. "Mining browsing and purchasing behaviors of web users." In 2010 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2010. http://dx.doi.org/10.1109/icmlc.2010.5580913.

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Reports on the topic "Users’ behaviors"

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Hall, Troy E., and David N. Cole. Changes in the motivations, perceptions, and behaviors of recreation users: Displacement and coping in wilderness. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2007. http://dx.doi.org/10.2737/rmrs-rp-63.

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Sarofim, Samer, and Aly Tawfik. Creating Safer Communities for the Use of Active Transportation Modes in California: The Development of Effective Communication Message Strategy for Vulnerable Road Users. Mineta Transportation Institute, July 2022. http://dx.doi.org/10.31979/mti.2021.2030.

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Despite increased efforts to improve safety in recent years (e.g., the Focus Cities Program in California), California continues to have a high rate of pedestrian and bicyclist fatalities. Currently, the state currently lacks a cohesive messaging strategy to improve behaviors related to pedestrian and cyclist traffic safety practices. To fulfill this need, this research showcases the differential effect of message framing on attitudes and intended behaviors related to pedestrian and cyclists traffic safety practices. This project investigated factors & risky behaviors contributing to accidents involving vulnerable road users, preventive measures to decrease accidents involving vulnerable road users, and more. The qualitative analysis presented a significant lack of coherent, long-term, evidence-based communication strategies that aimed at enhancing the safety of vulnerable road users in California. Quantitatively, this research also experimentally investigated various messages, employing different time horizons and regulatory focus message framings. Findings indicate that the messages with a limited time horizon tend to be associated with better safety perceptions and attitudes than messages with an expansive time horizon. California transportation authorities, professionals, and advocacy groups will be able to use this information to effectively allocate the communication effort and spending to induce attitudinal and behavioral change that can impact the safety of active transportation modes.
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Sarofim, Samer, and Aly Tawfik. Creating Safer Communities for the Use of Active Transportation Modes in California: The Development of Effective Communication Message Strategy for Vulnerable Road Users. Mineta Transportation Institute, July 2022. http://dx.doi.org/10.31979/mti.2022.2030.

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Despite increased efforts to improve safety in recent years (e.g., the Focus Cities Program in California), California continues to have a high rate of pedestrian and bicyclist fatalities. Currently, the state currently lacks a cohesive messaging strategy to improve behaviors related to pedestrian and cyclist traffic safety practices. To fulfill this need, this research showcases the differential effect of message framing on attitudes and intended behaviors related to pedestrian and cyclists traffic safety practices. This project investigated factors & risky behaviors contributing to accidents involving vulnerable road users, preventive measures to decrease accidents involving vulnerable road users, and more. The qualitative analysis presented a significant lack of coherent, long-term, evidence-based communication strategies that aimed at enhancing the safety of vulnerable road users in California. Quantitatively, this research also experimentally investigated various messages, employing different time horizons and regulatory focus message framings. Findings indicate that the messages with a limited time horizon tend to be associated with better safety perceptions and attitudes than messages with an expansive time horizon. California transportation authorities, professionals, and advocacy groups will be able to use this information to effectively allocate the communication effort and spending to induce attitudinal and behavioral change that can impact the safety of active transportation modes.
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Scrivens, Ryan, Steven M. Chermak, Joshua D. Freilich, Thomas W. Wojciechowski, and Richard Frank. Detecting Extremists Online: Examining Online Posting Behaviors of Violent and Non-Violent Right-Wing Extremists. RESOLVE Network, September 2021. http://dx.doi.org/10.37805/pn2021.21.remve.

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Like most of us, violent extremists often leave a digital footprint behind. Researchers, practitioners, and policymakers raise questions about whether violent individuals can be identified online prior to their attacks offline based on their online posting behaviors. Despite ongoing concerns, few empirically grounded analyses have identified which online users have engaged in violent extremism offline and then assessed their digital footprints, and fewer analyses have identified differences in posting behaviors of those who share extreme ideological beliefs but are violent or non-violent in the offline world. This policy note highlights the importance of both identifying and examining the online behaviors of violent and non-violent extremists in preventing and countering violent extremism (P/CVE) and provides researchers, practitioners, and policymakers with a number of recommendations for detecting and analyzing the online behaviors of violent and non-violent extremists in the future.
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Bobashev, Georgiy, John Holloway, Eric Solano, and Boris Gutkin. A Control Theory Model of Smoking. RTI Press, June 2017. http://dx.doi.org/10.3768/rtipress.2017.op.0040.1706.

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We present a heuristic control theory model that describes smoking under restricted and unrestricted access to cigarettes. The model is based on the allostasis theory and uses a formal representation of a multiscale opponent process. The model simulates smoking behavior of an individual and produces both short-term (“loading up” after not smoking for a while) and long-term smoking patterns (e.g., gradual transition from a few cigarettes to one pack a day). By introducing a formal representation of withdrawal- and craving-like processes, the model produces gradual increases over time in withdrawal- and craving-like signals associated with abstinence and shows that after 3 months of abstinence, craving disappears. The model was programmed as a computer application allowing users to select simulation scenarios. The application links images of brain regions that are activated during the binge/intoxication, withdrawal, or craving with corresponding simulated states. The model was calibrated to represent smoking patterns described in peer-reviewed literature; however, it is generic enough to be adapted to other drugs, including cocaine and opioids. Although the model does not mechanistically describe specific neurobiological processes, it can be useful in prevention and treatment practices as an illustration of drug-using behaviors and expected dynamics of withdrawal and craving during abstinence.
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Sarofim, Samer. Developing an Effective Targeted Mobile Application to Enhance Transportation Safety and Use of Active Transportation Modes in Fresno County: The Role of Application Design & Content. Mineta Transportation Institute, July 2021. http://dx.doi.org/10.31979/mti.2021.2013.

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This research empirically investigates the need for, and the effective design and content of, a proposed mobile application that is targeted at pedestrians and cyclists in Fresno County. The differential effect of the proposed mobile app name and colors on the target audience opinions was examined. Further, app content and features were evaluated for importance and the likelihood of use. This included design appeal, attractiveness, relevance, ease of navigation, usefulness of functions, personalization and customization, message recipients’ attitudes towards message framing, and intended behaviors related to pedestrian, cyclist, and motorist traffic safety practices. Design mobile application features tested included image aesthetics, coherence and organization, and memorability and distinction. Potential engagement with the mobile app was assessed via measuring the users’ perceived enjoyment while using the app. The behavioral intentions to adopt the app and likelihood to recommend the app were assessed. The willingness to pay for purchasing the app was measured. This research provided evidence that a mobile application designed for pedestrians and cyclists is needed, with high intentions for its adoption. Functions, such as Safety Information, Weather Conditions, Guide to Trails, Events for Walkers and Bikers, and Promotional Offers are deemed important by the target population. This research was conducted in an effort to increase active transportation mode utilization and to enhance the safety of vulnerable road users. The public, city administrators, transportation authorities, and policy makers shall benefit from the results of this study by adapting the design and the features that are proposed in this research and were found appealing and useful for the target vulnerable road user groups. The need of the proposed mobile application and its main functions are established, based on the results of this research, which propagates further steps of implementation by city administrators and transportation authorities.
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Raju, Saraswati, and Ann Leonard. Men as Supportive Partners in Reproductive Health: Moving from Rhetoric to Reality. Population Council, 2000. http://dx.doi.org/10.31899/rh2000.1040.

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This book builds on presentations of the Workshop on Men as Supportive Partners in Reproductive and Sexual Health held in Kathmandu, Nepal, in 1998. By analyzing the experiences of nongovernmental organizations across India, this publication reviews important concerns that should inform the discourse on male partnership. The previous views of reaching men as contraceptive users and removing them as impediments to women’s efforts to control fertility are too limited. The argument is not whether men and women should use family planning, but rather the extent to which men can become supportive of women’s reproductive and sexual rights and actively take part in responsible and healthy reproductive behavior. Applied research is needed to learn how to stimulate and support positive and healthy sexual partnerships between women and men. It is important to demonstrate that contraceptive safety and continuation, safer sexual behaviors, use of reproductive health services, reduction in morbidity and mortality, and other health outcomes can be improved through the positive involvement of men as supportive partners and responsible parents. This publication provides a wealth of information on male partnership issues.
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Turcotte, Melissa, and Juston Shane Moore. User Behavior Analytics. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1345176.

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Turcotte, Melissa, Francesco Sanna Passino, Juston Shane Moore, and Nicholas Heard. User Behaviour Analytics. Office of Scientific and Technical Information (OSTI), March 2019. http://dx.doi.org/10.2172/1501758.

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Brooks, Rodney. The Behavior Language; User's Guide. Fort Belvoir, VA: Defense Technical Information Center, April 1990. http://dx.doi.org/10.21236/ada225808.

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