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Showing 63 results for Behavior
- Khadije Akar, - Mohammad Reza Kiani, - Mahmood Sangari,
Volume 11, Issue 2 (9-2024)
Volume 11, Issue 2 (9-2024)
Abstract
Introduction
Online social networks are new and innovative media that have made changes in the social, cultural, economic and political structures of societies. These networks have not only changed the rules and regulations governing communication and interaction between humans, but also our thinking and attitude towards ourselves, others and the world. With the rapid development of technology, online social networks have become very popular in the current decade.
With the development of virtual space and the use of social networks, privacy is at risk more than ever, and in the meantime, social networks have a privileged status in terms of obtaining, collecting and using personal information. There are several security and privacy issues related to shared user information, especially when a user uploads personal content such as photos, videos, and audio files.
Methods and Materoal
This descriptive survey used a Researcher-made questionnaire on a sample of students of University of Birjand (375 participants). For questionnaire’s validity, the experts’ opinions was used, and Cronbach's alpha was used for questionnaire’s reliability (0.876).
Resultss and Discussion
The increasing daily use of online social networks around the world leads to more problems regarding the security and privacy behavior of users in this attractive environment. While users can enjoy many benefits by using the service, at the same time they have many concerns about the privacy of their information. Despite privacy concerns, users continue to use these platforms and continue to share or self-disclose more personal information. Now, in order to deal with these threats, it is necessary to know what factors affect the security and privacy in social networks. According to many researches that have been conducted in this field, there are many factors that influence, but the factors that the current research focused on (after examining the level of awareness and importance of users to the two categories of security and privacy), two factors are individual factors and social engineering. was Individual factors being the factors that caused users to fail to use private settings, and social engineering was actually the abuse of trust or the deception of human agents to access confidential information and then abuse this information.
The results showed that although the respondents attached great importance to topics related to security and privacy, they admitted that they were less aware of many of these topics than expected. The results of the next questions showed that the behaviors related to individual factors were less than expected among the respondents, while the behaviors related to social engineering were within the expected range and even beyond. Examining the demographic variables showed that women received a higher score than men in all the investigated variables. Also, the scores of undergraduate students from two levels higher than theirs were higher in all variables.
Conclusion
In today's interconnected world, many relationships and interactions with others are virtual and they have provided easy conditions for exchanging information, news, events with the ability to comment and share information with a wide audience and even create content. Therefore, social media has attracted more and more attention. This volume of information exchange has put the security and privacy of users in social networks at risk. To deal with these threats, users must know what factors affect security and privacy. Among the broad factors that have been mentioned in previous studies, the most important factors have been discussed in the current research, which can be called individual factors and social engineering. Now, considering the need to clarify the issue, in this research, the role of individual factors and social engineering in the behaviors related to the security and privacy of users in social networks has been discussed.
The results of the questions confirmed that students, as active members of the society, are not as aware of issues related to security and privacy as they should be, and the percentage of this awareness was less than expected, but contrary to their relatively low awareness, fortunately, security and privacy are very important. They were private in social networks. Although it was expected that students, as an informed and cultured segment of the academic community, would have acceptable knowledge in the field of security and privacy, but unfortunately, the result of the present study was the opposite, and this is an alarm for all university and government officials who think about education and to inform the students.
On the other hand, it is true that students attach great importance to their security and privacy in social networks, but certainly to realize this issue and actually its prerequisite, to be familiar with the rules of the privacy policy and how to make security and privacy settings. It is that until this important thing is not done correctly, the issue of giving importance to security and privacy cannot be given proper attention, even though this issue is important for students
Dr. Afshin Hamdipour, Dr. Hashem Atapour, Negin Kajaiee,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
Information Seeking Behavior is a broad term encompassing a series of actions undertaken to articulate individuals’ information needs, search for information, evaluate it and select relevant data, ultimately leading to its use (Ozowa and Aba, 2017). According to Case and Given (2016), information-seeking is an integral part of human life. They note that humans frequently feel the need for information and actively seek it throughout their daily lives. In their research, which examined the information-seeking behaviors of professionals from various fields, including physicians, nurses, managers, engineers, journalists, customers, and other groups, the authors found significant differences in the information-seeking behaviors of various professions. These differences can be attributed to professional roles, work environments, and specific information needs. As a dimension of human behavior, information-seeking is influenced by numerous factors. Given the critical role of psychological aspects in shaping human information-seeking behavior and their impact on the interaction between humans and information, addressing these factors is vital. The increasing focus on user-centered (human-centered) studies in recent decades highlights the importance of such studies. This research explores personality traits that influence the information-seeking behavior of graduate students at the University of Tabriz.
Methods and Materials
This study used a descriptive-survey method. The statistical population comprised 2,826 graduate students (2,258 master’s and 568 doctoral students from 17 faculties at the University of Tabriz, excluding dependent units and the international campus, during the first semester of the 2022-2023 academic year. The students were enrolled in four fields: humanities, basic sciences, engineering, and agriculture. Using Cochran’s formula, the sample size was calculated to be 338 students selected through stratified random sampling. The study employed a localized version of John and Srivastava’s (1999) questionnaire for data collection. The questionnaire included two sections: six demographic items and 42 items rated on a five-point Likert scale to assess information-seeking behavior and five personality traits (Extraversion, Conscientiousness, Agreeableness, Openness to Experience, Neuroticism). Validity was ensured through expert review by five faculty members, and reliability was confirmed using Cronbach’s alpha, with coefficients ranging from 0.588 to 0.903. Data were analyzed using descriptive statistics (frequency, mean, standard deviation) and inferential statistics (multiple linear regression). Skewness and kurtosis coefficients that fell within ±2 confirmed the normal distribution of the data.
Results and Discussion
The findings of the present study showed that all five dimensions of personality traits (extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism with averages of 4.13, 3.94, 3.99, 4.11, and 2.69 respectively) have a significant effect on the information-seeking behavior of graduate students at Tabriz University; Specifically, Extraversion, Conscientiousness, Agreeableness, and Openness to Experience demonstrated positive effects, while Neuroticism exhibited a negative effect. Other results showed that among information-seeking behaviors, "referring to the Internet to obtain information" has the highest priority among students, with an average of 4.72. In the extraversion dimension, "being friendly in the process of acquiring information" is the most important, with an average of 4.34. In the dimension of conscientiousness, "observance of order in the process of obtaining information" has the highest average score, with an average score of 4.22. In the adaptability dimension, "tendency to cooperate with others during information searching" has the highest score with an average of 4.29. In the experience acceptance dimension, "having an active imagination in the information seeking process" has the highest rank with an average of 4.42. In the dimension of neuroticism, "being nervous in the process of finding information" is the highest average score (3.03). The results of multiple linear regression also showed that the independent variables, extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism are significant predictors of information-seeking behavior, which explain 25.6% of the changes related to the dependent variable. Among the 5 independent variables, the conscientiousness variable, with a beta coefficient of 0.220, made a greater contribution than the other variables.
Conclusion
The findings of this study confirmed the effect of five important personality traits on information-seeking behavior. It is expected that librarians and information specialists will consider the different aspects of personality traits in information-seeking behavior and pay attention to the fact that knowledge of these issues will help them to provide effective information services to students. According to the findings of the present study, it is recommended that the libraries of University of Tabriz establish information systems based on individual student differences to facilitate an optimal environment for information searching. In addition, organizing workshops on communication skills can help students perform more effectively in information-seeking activities. These skills can be beneficial for both extroverted and even neurotic students. It is also recommended that information system designers tailor their systems and services based on the needs and personality traits of students. Furthermore, it is recommended that librarians receive the necessary training to identify students’ individual characteristics and differences and provide information services tailored to their personality traits during interactions with users. Finally, offering psychological counseling and stress management support for students can help them reduce their anxiety and improve their performance in information-seeking activities. This is particularly beneficial for students with high neuroticism levels.
Methods and Materials
This study used a descriptive-survey method. The statistical population comprised 2,826 graduate students (2,258 master’s and 568 doctoral students from 17 faculties at the University of Tabriz, excluding dependent units and the international campus, during the first semester of the 2022-2023 academic year. The students were enrolled in four fields: humanities, basic sciences, engineering, and agriculture. Using Cochran’s formula, the sample size was calculated to be 338 students selected through stratified random sampling. The study employed a localized version of John and Srivastava’s (1999) questionnaire for data collection. The questionnaire included two sections: six demographic items and 42 items rated on a five-point Likert scale to assess information-seeking behavior and five personality traits (Extraversion, Conscientiousness, Agreeableness, Openness to Experience, Neuroticism). Validity was ensured through expert review by five faculty members, and reliability was confirmed using Cronbach’s alpha, with coefficients ranging from 0.588 to 0.903. Data were analyzed using descriptive statistics (frequency, mean, standard deviation) and inferential statistics (multiple linear regression). Skewness and kurtosis coefficients that fell within ±2 confirmed the normal distribution of the data.
Results and Discussion
The findings of the present study showed that all five dimensions of personality traits (extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism with averages of 4.13, 3.94, 3.99, 4.11, and 2.69 respectively) have a significant effect on the information-seeking behavior of graduate students at Tabriz University; Specifically, Extraversion, Conscientiousness, Agreeableness, and Openness to Experience demonstrated positive effects, while Neuroticism exhibited a negative effect. Other results showed that among information-seeking behaviors, "referring to the Internet to obtain information" has the highest priority among students, with an average of 4.72. In the extraversion dimension, "being friendly in the process of acquiring information" is the most important, with an average of 4.34. In the dimension of conscientiousness, "observance of order in the process of obtaining information" has the highest average score, with an average score of 4.22. In the adaptability dimension, "tendency to cooperate with others during information searching" has the highest score with an average of 4.29. In the experience acceptance dimension, "having an active imagination in the information seeking process" has the highest rank with an average of 4.42. In the dimension of neuroticism, "being nervous in the process of finding information" is the highest average score (3.03). The results of multiple linear regression also showed that the independent variables, extroversion, conscientiousness, adaptability, acceptance of experience, and neuroticism are significant predictors of information-seeking behavior, which explain 25.6% of the changes related to the dependent variable. Among the 5 independent variables, the conscientiousness variable, with a beta coefficient of 0.220, made a greater contribution than the other variables.
Conclusion
The findings of this study confirmed the effect of five important personality traits on information-seeking behavior. It is expected that librarians and information specialists will consider the different aspects of personality traits in information-seeking behavior and pay attention to the fact that knowledge of these issues will help them to provide effective information services to students. According to the findings of the present study, it is recommended that the libraries of University of Tabriz establish information systems based on individual student differences to facilitate an optimal environment for information searching. In addition, organizing workshops on communication skills can help students perform more effectively in information-seeking activities. These skills can be beneficial for both extroverted and even neurotic students. It is also recommended that information system designers tailor their systems and services based on the needs and personality traits of students. Furthermore, it is recommended that librarians receive the necessary training to identify students’ individual characteristics and differences and provide information services tailored to their personality traits during interactions with users. Finally, offering psychological counseling and stress management support for students can help them reduce their anxiety and improve their performance in information-seeking activities. This is particularly beneficial for students with high neuroticism levels.
Dr. Mohammad Moradi,
Volume 11, Issue 3 (12-2024)
Volume 11, Issue 3 (12-2024)
Abstract
Social networks and their increasing influence among different users in all parts of the world have made these networks become suitable tools for advertising and e-commerce. Today, businesses have come to understand that social networks are and will continue to be a means of doing business. Instagram is a popular social network based on video and images. This social network is known as one of the powerful marketing tools. The number of views, likes and comments on social networks, including Instagram, plays a significant role in customer decision-making; Because they pay attention to the opinions and reception of other audiences towards that product or post and are influenced. This research analyzes what factors create posts with different levels of popularity. For this purpose, the factors affecting the number of views, likes and comments in an Instagram social network post are extracted and their weight and importance are calculated based on the regression model. Finally, the decision tree model is presented for forecasting and management in order to increase the number of visits, likes and comments.
Methods and Materoal
In this research, the type of research is based on the purpose of applied research. At first, library studies have been used in order to extract factors affecting the amount of visits, likes and comments in Instagram social network marketing posts. The statistical population includes all articles related to the factors affecting visits, likes and comments. The probability sampling method of simple random samples has been used and 30 articles in this field have been reviewed. Then, the data related to the factors identified from the previous stage have been extracted from the pages of big marketers on the Instagram social network. Then, using the extracted data and using the regression model, the weight and importance of each factor affecting the number of visits, likes, and comments of Instagram social network marketers' posts has been calculated. Finally, a decision tree model has been created to predict the status (rate of visits, likes and comments) of a marketing post on the Instagram social network based on the characteristics of that post.
Resultss and Discussion
Directly, factors such as the number of posts, the number of followers, the type of post, the content of the post and the time of the post are potential factors that affect the number of views, likes and comments. According to the obtained results, the "post content with survey" factor with a positive sign and a coefficient of 420,290.616 had the most positive effect on the label, which is the number of visits to a post. The factor "discount post content" with a positive sign and a coefficient of 5417.751 has had the most positive effect on the label, which is the liking of a post. The factor "discount post content" with a positive sign and a coefficient of 2164.016 has had the most positive effect on the label, which is the amount of comments on a post. Also, the type of image post with a regression coefficient of 565.153 and a negative sign in the investigation of factors affecting the number of comments shows that the use of video posts will increase the comments and interaction of customers.
Conclusion
Most of the researches conducted, such as Gkikas et al (2022), Torbarina, Jelenc & Brkljačić (2020), Wahid & Gunarto (2022), etc., only investigated the influence of a few specific factors on the likes and comments of social media posts, and a comprehensive set of factors has not been investigated. Also, these factors were only for checking likes or opinions and not checking both cases. Most importantly, in the studies conducted, only the positive or negative impact of a factor on the number of likes and opinions has been discussed, and their importance has not been determined. In this research, various factors affecting the number of visits, likes and comments of social network posts were investigated. Also, the importance of each factor was determined. In addition, a decision tree model was presented to manage related pages and posts in order to achieve increased likes and comments. Based on the extracted effective factors, calculating the weight and importance of each factor and the created decision tree model, posts can be managed to increase the number of visits, likes and comments
Methods and Materoal
In this research, the type of research is based on the purpose of applied research. At first, library studies have been used in order to extract factors affecting the amount of visits, likes and comments in Instagram social network marketing posts. The statistical population includes all articles related to the factors affecting visits, likes and comments. The probability sampling method of simple random samples has been used and 30 articles in this field have been reviewed. Then, the data related to the factors identified from the previous stage have been extracted from the pages of big marketers on the Instagram social network. Then, using the extracted data and using the regression model, the weight and importance of each factor affecting the number of visits, likes, and comments of Instagram social network marketers' posts has been calculated. Finally, a decision tree model has been created to predict the status (rate of visits, likes and comments) of a marketing post on the Instagram social network based on the characteristics of that post.
Resultss and Discussion
Directly, factors such as the number of posts, the number of followers, the type of post, the content of the post and the time of the post are potential factors that affect the number of views, likes and comments. According to the obtained results, the "post content with survey" factor with a positive sign and a coefficient of 420,290.616 had the most positive effect on the label, which is the number of visits to a post. The factor "discount post content" with a positive sign and a coefficient of 5417.751 has had the most positive effect on the label, which is the liking of a post. The factor "discount post content" with a positive sign and a coefficient of 2164.016 has had the most positive effect on the label, which is the amount of comments on a post. Also, the type of image post with a regression coefficient of 565.153 and a negative sign in the investigation of factors affecting the number of comments shows that the use of video posts will increase the comments and interaction of customers.
Conclusion
Most of the researches conducted, such as Gkikas et al (2022), Torbarina, Jelenc & Brkljačić (2020), Wahid & Gunarto (2022), etc., only investigated the influence of a few specific factors on the likes and comments of social media posts, and a comprehensive set of factors has not been investigated. Also, these factors were only for checking likes or opinions and not checking both cases. Most importantly, in the studies conducted, only the positive or negative impact of a factor on the number of likes and opinions has been discussed, and their importance has not been determined. In this research, various factors affecting the number of visits, likes and comments of social network posts were investigated. Also, the importance of each factor was determined. In addition, a decision tree model was presented to manage related pages and posts in order to achieve increased likes and comments. Based on the extracted effective factors, calculating the weight and importance of each factor and the created decision tree model, posts can be managed to increase the number of visits, likes and comments
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