Behavior In Social Networks Research Articles

Collecting and analyzing news from newspaper posts in facebook using machine learning

Many people use social networks to spend their free time. News, especially at the time of great world changes, began to gain considerable popularity. Washington Post, New York Times, Time, Reuters, Forbes are among the most famous global newspaper publications. An average analyst can spend up to 40 hours a week collecting information about competitors and researching the most popular posts. According to the conducted research, an average of 40 new posts with news per day. The data processing process can be automated using modern information tools to facilitate the routine work of analysts. To analyze the target audience and reach, it is worth considering the text of the message, the number of likes, comments and links. This information was obtained using the Selenium automated web page testing tool using the Java programming language. The time spent on collecting data in the described way from four newspaper editions amounts to approximately 12 hours. The Tensorflow library using the JavaScript programming language is applied to the collected information. Based on information about the number of shares, comments, likes, frequency of news posts, an analysis was carried out using machine learning algorithms. Based on the clustering data, we can observe such a tendency that posts with a large number of likes receive a large number of comments and vice versa. An analysis of the most active hours of users in the network based on news posts is performed. As a result, the highest activity is observed at least three times a day, namely: in the morning hours from 9:00 to 11:00, in the lunch time of the day from 12:00 to 15:00 and in the evening time period from 18:00 to 20:00. This trend is due to the work schedule of most employees during the working week. The resulting statistical information in the work can be used for other content or user behavior in social networks.

A temporal graph framework for intelligence extraction in social media networks

Social media networks (SMNs) are increasingly used in professional management of knowledge workers and related assets. However, the factors affecting behavioral trends and activity levels in these networks are not well understood. Although social and cognitive theories can help to explain human behavior in traditional social networks, their application to SMNs has not been validated. Traditional social network modeling techniques may not accurately predict real-world SMN activities. This research developed a temporal graph framework for intelligence extraction in SMNs. Theory-based, data-driven models (Conformity Model (COM), Recency-Primacy Model (REM), Trend Interaction Model (TIM), Periodic Interaction Model (PIM)) were developed based on the framework to capture various aspects of user behavior: conformity effect, recency, primacy, periodicity, and dynamic trend. The models capture the activity history and dynamically combine pricing information to enhance predictive accuracy. Using data of 83,536 GitHub software repositories on cryptocurrency, this article reports the results of experiments that compare the models’ performance in predicting SMN activities over time. Experimental results show that the model (REM) that captures recency/primacy effects of human cognitive processing outperformed other models in 9 (out of 18) measures pertaining to engagement, contribution, influence, and popularity. Primacy plays a dominant role in predicting engagement, contribution, and popularity, whereas recency plays a key role in predicting influence. Short-term trend (modeled with TIM) was found to yield significantly better performance on predicting user contribution. The models also outperformed an integrated machine learning (IML) model by most measures. Overall, the effects modeled by REM and TIM were found to be more significant than the effects modeled by COM, PIM, and IML. The research contributes to enhancing understanding of SMN behavior, developing new models to simulate and predict SMN activities, and designing new artifacts for information systems practitioners to manage knowledge assets and to extract SMN intelligence.

Does brand community participation lead to early new product adoption? The roles of networking behavior and prior purchase experience.

Consumers' adoption behavior is critical to the success of new products, but the effects of brand communities on new product adoption have rarely been investigated. In this study, we draw on network theory to examine how consumer participation in brand communities (in terms of participation intensity and social networking behaviors) affects the adoption of new products. We collected longitudinal data from 8,296 members of an online community of a well-known smartphone brand to assess the factors influencing new product adoption. The results from applying a hazard model indicated that brand community participation increases the speed of adoption of new products. The positive effect of members' out-degree centrality on new product adoption was found to be significant, but in-degree centrality only had an effect when users had previous purchasing experience. These findings extend the literature by revealing how new products are disseminated across brand communities. The study also makes theoretical and practical contributions to the literature on brand community management and product marketing.

Social network and health behaviors among Japanese older adults: a three-wave longitudinal study.

Identifying modifiable determinants of behavior is essential for developing effective strategies to promote health behaviors among older adults. Although social networks are potentially modifiable determinants of health behaviors, their longitudinal associations have not been established in previous studies. The present study examined whether a larger social network is associated with higher dietary variety, longer time spent exercising and shorter time spent viewing TV among older adults. This is a longitudinal study. The data of 908 Japanese older adults were obtained through a three-wave questionnaire survey (Wave 1, December 2017 to January 2018; Wave 2, after 1 year; Wave 3, after 3 years) and analyzed. In each wave of the survey, dietary variety (dietary variety score), exercise time (hours per day), TV viewing time (hours per day) and social network (family and friend subscales of the Japanese version of the abbreviated Lubben Social Network Scale) were measured. The present study used latent growth, cross-lagged and simultaneous effect models to investigate the longitudinal associations of family and friend social networks with dietary variety, exercise time and TV viewing time. However, these models did not show clear and robust associations. Whether social networks are determinants of health behaviors among older adults remains inconclusive.

Analysis of Consumer Recommendation Behavior and Market Equilibrium in E-Commerce from the Perspective of Social Media

Under the strategic goal of building a domestic economic cycle, the development quality of social e-commerce in my country needs to be improved urgently. The main reason for the low quality of social e-commerce development in my country is that the natural advantages of social e-commerce, such as high-efficiency dissemination of information and increased consumer utility due to improper sales model design, cannot play a role. However, the lack of research on social e-commerce systems makes it difficult for retailers to obtain effective theoretical guidance for their sales model design. Based on this, this paper takes the three most important and important social e-commerce sales models in my country at present—recommended reward model, online group purchase model, and online crowdfunding model as the research objects, and systematically analyzes the consumer recommendation behaviors in the three sales models. By analyzing and market equilibrium, while improving the theoretical research of social e-commerce, it also provides theoretical basis and policy guidance for the optimal mode design of social e-commerce under different sales modes. This paper considers the consumer recommendation behavior in social networks and analyzes the main characteristics of the three sales models in view of the development status and specific problems of social e-commerce in my country, and then constructs retailer-existing consumer-potential The three-agent dynamic Stackelberg game model of consumers analyzes the influence mechanism and market equilibrium of consumer recommendation behavior under three sales models.

Toward Network Intelligence.

This article proposes a conceptual framework to guide research in neural computation by relating it to mathematical progress in other fields and to examples illustrative of biological networks. The goal is to provide insight into how biological networks, and possibly large artificial networks such as foundation models, transition from analog computation to an analog approximation of symbolic computation. From the mathematical perspective, I focus on the development of consistent symbolic representations and optimal policies for action selection within network settings. From the biological perspective, I give examples of human and animal social network behavior that may be described using these mathematical models.

Mediation of transgender impression management between transgender privacy paradox and Trans Facebook Persona: A trans perspective

This study builds and evaluates a transgender privacy paradox impression management (TPPIM)' model to examine the influence of social networking site impression management (IM) on transgender users' sustained SNS involvement, contributing a new view to the field of information systems research. The study finds no direct relationship between privacy paradox and transgender individuals' online social media persona. However, transgender individuals, to enjoy an uninterrupted social media presence and protect their privacies, employ various impression management strategies on social media, which fully mediate the relationship between the privacy paradox and their social media personas. Transgender individuals use their social media presence to find resources required for their day-to-day survival, indicating that an active social media presence is not optional but mandatory. Users value privacy, however, they consciously or unconsciously implement privacy averseness for an active social media presence. The authors use a mixed methodology where qualitative analysis findings informed hypotheses and model development of a structural model that used 299 useable responses and PLS/SEM to test and confirm that trans impression management mediates the relationship between the trans privacy paradox and transgender persons' Facebook behavior. This study enhances model complexity relative to earlier work, mediating the investigation's hypothesized behavioral correlations. Complementing current SNS research, it highlights the complexity of social networking behavior, the suitability of impression management theory to describe dynamically evolving social structures, and how social capital drives impression management.

A Personalized Explainable Learner Implicit Friend Recommendation Method

With the rapid development of social networks, academic social networks have attracted increasing attention. In particular, providing personalized recommendations for learners considering data sparseness and cold-start scenarios is a challenging task. An important research topic is to accurately discover potential friends of learners to build implicit learning groups and obtain personalized collaborative recommendations of similar learners according to the learning content. This paper proposes a personalized explainable learner implicit friend recommendation method (PELIRM). Methodologically, PELIRM utilizes the learner's multidimensional interaction behavior in social networks to calculate the degrees of trust between learners and applies the three-degree influence theory to mine the implicit friends of learners. The similarity of research interests between learners is calculated by cosine and term frequency–inverse document frequency. To solve the recommendation problem for cold-start learners, the learner's common check-in IP is used to obtain the learner's location information. Finally, the degree of trust, similarity of research interests, and geographic distance between learners are combined as ranking indicators to recommend potential friends for learners and give multiple interpretations of the recommendation results. By verifying and evaluating the proposed method on real data from Scholar.com, the experimental results show that the proposed method is reliable and effective in terms of personalized recommendation and explainability.

PROSOCIAL BEHAVIOR OF TEENAGERS IN SOCIAL NETWORKS

Relevance. Prosocial behavior in social networks is a manifestation of digital socialization, which includes voluntary behavior in an online environment in order to benefi t specifi c people or promote harmonious relationships with others. Prosociality on the Internet includes the exchange of resources and information, emotional support and online help. The purpose of the study is to evaluate the frequency and manifestations of prosocial experience of adolescents in social networks. Research methods. To assess prosocial behavior in online mode, the self-reporting methodology “Online prosocial behavior of adolescents” (OPBS) S. Erreygers, , and scales of performing and receiving prosocial behavior online were used. Sample.  teenagers aged - (M=.) from secondary schools and colleges of the Ivanovo region took part in the survey. The main results. The study showed that () adolescents have experience of performing prosocial behavior on the Internet above average (M= out of ); () adolescents perform prosocial behavior online more often than they receive it in response (by %); () teenage girls perform and receive prosocial behavior more often than teenage boys (by .% and %, respectively); () the most frequent type of prosocial behavior in social networks is emotional support for others (I cheered someone up) and relationship support (I said friendly words to someone, I made a compliment), the least frequent is an open display of sympathy (I made it clear that I like him) and help with homework at school (I helped with homework). Conclusion. The prosocial activity of adolescents in social networks, as well as in offl ine mode, is aimed at maintaining interpersonal relationships with peers and is less associated with assistance in educational activities. Prosocial online contacts promote safe behavior in social networks, increase the social capital of adolescents, and serve as a means of preventing Internet risks.

Вербальні вияви агресії в соціальних мережах (на матеріалі анкетування здобувачів спеціальності «Журналістика»)

Introduction. In modern linguistics, research into various manifestations of verbal aggression has intensified, particularly in social networks. The priority of the state policy of Ukraine is to ensure the protection of life and health, including mental health, of participants in the educational environment, therefore, in the process of working with students of higher education, the question of the nature of aggression, its forms, ways of spreading and prevention inevitably arises. Purpose. The article analyzes the phenomenon of verbal aggression as a form of conflictogenic speech behavior in social networks; based on the material of an anonymous survey of students majoring in "Journalism", the level of awareness of students of higher education regarding verbal aggression in the virtual space was determined, and the linguistic means of implementing aggression in the form of ridicule (mockery), disrespectful comments, threats (intimidation) were characterized. Methods. The main method of research iss anonymous questionnaire of students, the questions of the questionnaire are aimed at determining the linguistic means of aggression in social networks. Results. The results of the anonymous survey of students majoring in "Journalism" regarding the manifestations of verbal aggression in the virtual space show that only 55 % of respondents are informed about verbal violence in social networks, 27 % of survey participants recognized themselves as the object of bullying. When answering other questions of the questionnaire, students testified to more cases of verbal aggression towards themselves, including verbal insults, mockery, intimidation, etc. Originality. The relevance of our investigation is due to the strengthening of the processes of speech aggression in general and the insufficiency of studying the problem of verbal violence in the virtual communicative space, in particular, among students. Conclusion. The results of the anonymous survey of students of higher education majoring in "Journalism" regarding verbal aggression as a form of conflict-causing speech behavior in social networks indicate the need to strengthen work with future media professionals to develop their ability to recognize manifestations of violence and adequately respond to them. In general, we note significant gaps in the knowledge of students of higher education of the speciality "Journalism" regarding verbal aggression - 45% of respondents do not have information about verbal violence in the virtual space. Questionnaire participants singled out the following hierarchy of forms of verbal aggression: disrespectful comments, ridicule (taunting), threats (intimidation), they primarily related to the appearance, behavior, and style of clothing of communicators; language means of aggression are defined as insulting statements, absent vocabulary, jokes (mostly without specification).

ДИЛЕМА ДВОЗНАЧНОСТІ У РОЗУМІННІ ПЕРСОНАЛЬНОГО БРЕНДУ

Informatization of all areas of modern human activity and the rapid development of new information and communication technologies create favorable conditions for the implementation of programs of operational access to remote material and intellectual resources distributed throughout the globe. Over the past decade, social media has changed the way people, communities, and organizations create, share, and consume information from each other and businesses. However, today people have become more careful about their presence on the Internet, especially on social networks. It is becoming increasingly clear that social media poses enormous risks to individuals, communities, companies, and even society as a whole. Examples of such risks in social media include cyberbullying, addictive use, trolling, online witch-hunts, fake news, and privacy violations. The credibility of our study was enhanced by detailed data collection aimed at obtaining a deeper understanding of the phenomena of personal perception of social networks based on primary data obtained from interviews with social network experts and secondary data from the analysis of a large amount of secondary data (industry reports, press releases, eSports columns, and blogs). Using a reverse approach with primary and secondary data, we were able to ensure that all information based on the secondary data set was consistent with the expert interviews, and this was the basis for our interviewee research. As part of this process, we asked our interviewees to describe the motivational factors behind their involvement in social networks. The main goal of this study was based on the multidimensionality and duality of individual perceptions of social networks. Applying a qualitative methodological approach, the article investigates the individual attitude of consumers toward behavior in social networks (SNS). Through the prism of personal brand development, it is understood that people strive to create a satisfactory presentation of the desired self. At the same time, an important criterion of individual behavior in social networks is the preservation of public perception of one's identity. The fear of being unclear is associated with conflicting opinions in front of the target audience. In addition to promotion, the research helps to understand how personal brand interests influence social perception. The obtained results help to gain more knowledge about consumers from the point of view of their involvement in marketing communication.

ДИЛЕМА РОЗВИТКУ ПЕРСОНАЛЬНОГО БРЕНДУ: БУТИ ЧИ НЕ БУТИ

Informatization of all areas of modern human activity and the rapid development of new information and communication technologies create favorable conditions for the implementation of programs of operational access to remote material and intellectual resources distributed throughout the globe. Over the past decade, social media has changed the way people, communities, and organizations create, share, and consume information from each other and businesses. However, today people have become more careful about their presence on the Internet, especially on social networks. It is becoming increasingly clear that social media poses enormous risks to individuals, communities, companies, and even society as a whole. Examples of such risks in social media include cyberbullying, addictive use, trolling, online witch-hunts, fake news, and privacy violations. The credibility of our study was enhanced by detailed data collection aimed at obtaining a deeper understanding of the phenomena of personal perception of social networks based on primary data obtained from interviews with social network experts and secondary data from the analysis of a large amount of secondary data (industry reports, press releases, eSports columns, and blogs). Using a reverse approach with primary and secondary data, we were able to ensure that all information based on the secondary data set was consistent with the expert interviews, and this was the basis for our interviewee research. As part of this process, we asked our interviewees to describe the motivational factors behind their involvement in social networks. The main goal of this study was based on the multidimensionality and duality of individual perceptions of social networks. Applying a qualitative methodological approach, the article investigates the individual attitude of consumers toward behavior in social networks (SNS). Through the prism of personal brand development, it is understood that people strive to create a satisfactory presentation of the desired self. At the same time, an important criterion of individual behavior in social networks is the preservation of public perception of one's identity. The fear of being unclear is associated with conflicting opinions in front of the target audience. In addition to promotion, the research helps to understand how personal brand interests influence social perception. The obtained results help to gain more knowledge about consumers from the point of view of their involvement in marketing communication.

Verbal manifestations of aggression in social networks (based on the questionnaire materials of higher education applicants of teaching specialties)

Introduction. In modern linguistics, research into various manifestations of verbal aggression has intensified, particularly in social networks. The priority of the state policy of Ukraine is to ensure the protection of life and health, including mental health, of participants in the educational environment, therefore, in the process of working with students of higher education in pedagogical specialties, the question of the nature of aggression, its forms, ways of spreading and prevention inevitably arises. Purpose. The article analyzes the phenomenon of verbal aggression as a form of conflictogenic speech behavior in social networks; based on the material of an anonymous survey of students of pedagogical specialties, the level of awareness of students of higher education regarding verbal aggression in the virtual space was determined, and the linguistic means of implementing aggression in the form of ridicule (mockery), disrespectful comments, threats (intimidation) were characterized. Methods. Anonymous questionnaire of students was the main method of research, since the questions of the questionnaire are aimed at determining the linguistic means of aggression in social networks. Results. The results of the anonymous survey of students of pedagogical specialties regarding the manifestations of verbal aggression in the virtual space reveal that only 60% of respondents are informed about verbal violence in social networks, 15% of survey participants recognized themselves as the object of bullying. When answering other questions of the questionnaire, students testified to more cases of verbal aggression towards themselves, including verbal insults, mockery, intimidation, etc. Originality. The relevance of our investigation is due to the strengthening of the processes of speech aggression in general and the insufficiency of studying the problem of verbal violence in the virtual communicative space, in particular, among the student body. Verbal aggression is the most common type of violence in modern schools and the cause of psychological tension in the educational environment. Conclusion. The results of the anonymous survey of students of higher education in pedagogical specialties regarding verbal aggression as a form of conflict-causing speech behavior in social networks indicate the need to strengthen work with students to develop the ability to recognize manifestations of violence and adequately respond to them. In general, we note significant gaps in the knowledge of students of higher education in pedagogical specialties regarding verbal aggression - 40% of respondents do not have information about verbal violence in the virtual space. Answers to questionnaire questions are usually correct, mostly one-word, without elaborate reasoning, which we associate with students’ reluctance to analyze images, violation of privacy, etc. Questionnaire participants singled out the following hierarchy of forms of verbal aggression: disrespectful comments, ridicule (taunting), threats (intimidation), they primarily related to the appearance, behavior, and style of clothing of communicators; language means of aggression are defined as insulting statements, absent vocabulary, jokes (mostly without specification).

INFLUENCE OF THE BLOGOSPHERE ON MEANINGFUL LIFE STRATEGIES IN YOUNG PEOPLE

Today, for many young people, a high rating on the Internet is much more important than real achievements. This situation is created by modern types of earning on the web with creating accounts that are highly popular. The aim of the study was to suggest that the life-meaning orientations and motivational sphere of young people, active and inactive in social networks, may differ in structure. Methods included “Test of life orientations” by D.A.Leontiev, A.A. Rean’s questionnaire “Motivation for success and fear of failure”, K. Zamfi r’s methodology “Motivation of professional activity”. The sample of the study was formed of  young “bloggers” aged  to  years. For young people with inactive behavior in social networks, who have a higher level of internal motivation, activity itself is more important than for young people who are more active in social networks. The group of subjects with inactive behavior concentrates less on the desire to satisfy external motives: social recognition, an increase in the share of acquiring social and material benefi ts during work. Such a motivational complex of personality is recognized as more positive, since internal motivation is the strongest of the three presented. This is due to the stable activity of young people with inactive behavior in the blogosphere, carried out on the basis of internal motives. Young people with inactive behavior in social networks are distinguished by participation in social movements, volunteer groups and having a job or experience of additional earnings, where the basis of motivation is the ability to satisfy internal needs, to help other people that this activity brings. The absence of statistically signifi cant differences in the indicators of external positive motivation and external negative motivation can be explained by incomplete involvement in social activities of both groups, which means that the system of external motivation is not fully formed.

Social Media, Networks, and Students in the Context of the Educational Process

Social media and networks have opened new opportunities for individuals to learn and grow, regardless of their educational or professional background. The implications and challenges of technology in educational settings are not well understood, despite its widespread use and impact on students. The study aims to investigate students’ social networking behaviour in the form of the use of social networking sites during class in relation to their gender, age group, education, and place of residence and focuses on three age groups of students who are representatives of Generation Y and Generation Z because both generations are growing up and coming of age in the 21st century and have been exposed to digitization and digital transformation since early childhood. The research sample consisted of 278 students from public and private universities and high school graduates who expressed interest in studying at the university. The results show that all examined variables, except place of residence, have a significant but small effect on what students do on social networking sites during classes and the reasons why they use them. However, according to the results, the fact that students connect to social networks during class does not imply that they have a reduced interest in the subject matter being taught or the knowledge being acquired, which means that there is a significant opportunity to adapt the learning approach on these platforms.

РОЗШИРЕННЯ ІНСТРУМЕНТІВ МАРКЕТИНГ-МІКС ЧЕРЕЗ ЗАСТОСУВАННЯ РЕКОМЕНДАЦІЙНОГО МАРКЕТИНГУ

Informatization of all areas of modern human activity and the rapid development of new information and communication technologies create favorable conditions for the implementation of programs of operational access to remote material and intellectual resources distributed throughout the globe. Over the past decade social media has changed the way people communities and organizations create share and consume information from each other and from businesses. However today people have become more attentive to recommendations for the consumption of certain goods and services. It's becoming increasingly clear that social media offers significant opportunities to engage shoppers especially for consumer goods. Examples of such opportunities in social networks include recommendations sharing information about their products sharing experiences etc. The credibility of our study was enhanced by detailed data collection aimed at obtaining a deeper understanding of the WOM phenomenon based on primary data obtained during interviews with marketing company experts and secondary data from the analysis of a large amount of secondary data (industry reports press releases columns about eSports and blogs). Using a reverse approach with primary and secondary data we were able to ensure that all information based on the secondary data set was consistent with the expert interviews and this was the basis for our interviewee research. As part of this process we asked our respondents to describe the motivational factors behind their social media engagement. The main goal of this study was based on the multidimensionality and effectiveness of the interaction of referral marketing with classic marketing mix tools. Applying a qualitative methodological approach the article investigates the individual attitude of consumers to behavior in social networks. Through the prism of personal brand development it is understood that people tend to imitate other people and listen to their opinion. The obtained results help to gain more knowledge about consumers from the point of view of their involvement in marketing communication.

The Effect of Globalization on the Rise of LGBT in Indonesia Through Social Media Networks Instagram and Tiktok

This study discusses deviant sexual behavior In Social networks where LGBT people are looking for a place to realize and look for relationships that take place in certain parties that help and provide all the needs of LGBT organizations through social media. Based on the phenomenon of the emergence of attitudes of LGBT people to the public through Social Media. The author tries to express the phenomenon where LGBT people are not only silent in the era of Globalization as it is today, They also voice their rights in this country through their Social Media. Based on the results of this study, it is hoped that it can provide information and input for the wider community that LGBT people have been very widespread in Indonesia even in the city of Medan, so that we can avoid these actions and the community can refuse and the Medan city government is following up on LGBT people who have appeared themselves on Social Media.

Utilizing statistical physics and machine learning to discover collective behavior on temporal social networks

Computational social science has become a branch of social science that uses computationally intensive ways to investigate and model social phenomena. Exploitation on mathematics, physics, and computer sciences, and analytic approaches like Social Network Analysis (SNA), Machine Learning (ML), etc, develops and tests the theories of complex social phenomena. In the emerging environment of social media, the new characteristics of social collective behavior and its extensive phenomena have become the hot spot of common concern across many disciplines. In this paper, we propose a general quantitative framework to discover the social collective behavior in temporal social networks. The general framework incorporates the Time-Correlation Function (T.C.F.) in statistical physics and evolutionary approach in Machine Learning, and provides the quantitative evidence of the existence of social collective behavior. Results show collective behaviors are observed and there exists a tiny fraction of users whose behavior are constantly replicated by public, disregard of the behavior itself. Our method is assumption-independent and has the potential to be applied to various temporal systems.

Deepsentimodels: A Novel Hybrid Deep Learning Model for an Effective Analysis of Ensembled Sentiments in E-Commerce and S-Commerce Platforms

Social networks and media have gradually grabbed significant time from people’s lives to share and communicate information. Moreover, these social platforms also act as an emotional catalyst for expressing their feeling and views on different products, movies, and even national policies. Thus, it helps to understand people’s opinions and predict their behaviors in social networks, where it helps the entrepreneur improve their products or services. It is considered the most efficient method to understand the customer’s view on their product better. Since entrepreneurs are increasing exponentially, an intelligent system is required to understand people’s views on their products. Also, people use informal language to express their sentiments; it has become a daunting task to extract the sentiments that reflect the people’s attitude and feedback about the product. Therefore, this article suggests a novel hybrid deep learning system, consisting of bi-convolutional networks (B-CNN) and spotted hyena optimized long short term memory (SHOLSTM), for improved understanding of people’s feelings and the construction of intelligent recommendation systems for entrepreneurs. Many experiments have been conducted utilizing various datasets compared to other current hybrid deep learning methods, including long short-term memory (LSTM), convolutional neural networks (CNN), BIGRU, and attention classifiers. Accuracy is achieved as 99.4%, 99% precision, 99.2% recall, 99.2% F1-score is achieved, which suits these algorithms best for implementing the intelligent recommendation systems based on the different ensembled sentiments.

A Covert-Aware Anonymous Communication Network for Social Communication

To effectively protect the communication content and communication behavior of social networks, anonymous communication technologies are widely used. However, the anonymous communication networks represented by Tor and I2P lack the covertness of the control plane design, which leads to important user behavioral characteristics in the process of accessing anonymous communication networks. Therefore, network monitors can analyze users' communication behavior by tracking these characteristics. In this paper, the concept of covert measurement is proposed. On this basis, a software-defined anonymous communication network architecture is presented, which also considers the covertness of the anonymous communication network control plane and the data plane. According to the theoretical analysis and experimental results, the anonymous communication network architecture proposed in this paper has better anonymity and usability than traditional anonymous communication networks, such as Tor.