Spread Of Social Networks Research Articles

Topic Enhanced Sentiment Spreading Model in Social Networks Considering User Interest

Emotion is a complex emotional state, which can affect our physiology and psychology and lead to behavior changes. The spreading process of emotions in the text-based social networks is referred to as sentiment spreading. In this paper, we study an interesting problem of sentiment spreading in social networks. In particular, by employing a text-based social network (Twitter) , we try to unveil the correlation between users' sentimental statuses and topic distributions embedded in the tweets, then to automatically learn the influence strength between linked users. Furthermore, we introduce user interest to refine the influence strength. We develop a unified probabilistic framework to formalize the problem into a topic-enhanced sentiment spreading model. The model can predict users' sentimental statuses based on their historical emotional status, topic distributions in tweets and social structures. Experiments on the Twitter dataset show that the proposed model significantly outperforms several alternative methods in predicting users' sentimental status. We also discover an intriguing phenomenon that positive and negative sentiment is more relevant to user interest than neutral ones. Our method offers a new opportunity to understand the underlying mechanism of sentimental spreading in online social networks.

Geolocation for research purposes: geotags as a data source

The worldwide spread of social networks provides new opportunities to collect data for various applied research. The geotagging function, which is present in most social networks, is extremely useful in the case of spatial research. For urban researchers, this is more than just an opportunity to collect a huge amount of information about the behavior of people in space, but also to analyze the space itself. However, this type of data has both significant advantages and limitations. The article includes highlighting the most significant characteristics that urban researchers need to consider working with social networks: their volume (the ability to work with them as big data), non-reactivity (they are reproduced by the users themselves) and additional interpretations (they allow us to understand the meanings of certain elements of space for individual individuals or groups). The authors also illustrate the research opportunities provided by online data in combination with geotagging with various empirical examples.

Factors affecting the spread of multiple information in social networks.

Information spreading in social networks is affected by many factors. Based on a novel information spreading model with five spreading mechanisms, we analyzed and compared the influence of various factors on information spreading. Through a large number of simulation experiments, we found that: (1) K-shell layers have the greatest impact on information spreading; (2) distance between the two information sources, correlation coefficient between two types of information and social reinforcement also affect the information spreading. The analysis results of these factors will be helpful for us to predict the trend of information spreading and find effective strategies to control information spreading.

La representación de la mujer en la viñeta española: construcción y participación femenina

El auge del movimiento feminista en España tuvo lugar durante la transición, acontecimiento histórico que estuvo reflejado de alguna manera en las viñetas de los periódicos, sin embargo, la falocracia imperante hizo que sean los ilustradores masculinos los que representasen el papel que la mujer estaba desempeñando en ese momento, así se reconocen algunos autores importantes en la lucha por la igualdad de género, como Perich o Forges. El papel de la mujer, su imagen social, y el feminismo son representados en las viñetas desde el enfoque y la mirada del hombre, hecho que continúa vigente en la actualidad, donde los principales medios de difusión periodística españoles siguen contando con ilustradores masculinos, y no será hasta la expansión de las redes sociales cuando las mujeres empiecen a encontrar un espacio donde publicar sus ilustraciones, naciendo un subgénero que puede ser denominado como la “autovignette”, viñetas feministas con firma de mujer.

An Efficient Spreading Strategy Considering Information Decays and Partial Interactions Between People in Scale-Free Networks

Complex networks are extensively applied to study the dynamics of real systems, such as how information spreads in social networks. Most existing spreading strategies are studied based on simple information spreading model, such as the optimized compartmental models in epidemics. However, for information spreading in social networks, more complex social factors should be considered. In this paper, we build an information spreading model that involves information decays and partial interactions based on multi-agent modeling in scale-free networks. The positive effects of a set of vertices on the spreading efficiency are discovered based on the proposed information spreading model. On the basis of the positive effects of those vertices, we propose an efficient spreading strategy for extending the spreading in scale-free networks. Ten groups of Monte Carlo experiments are conducted to verify the effectiveness of the proposed strategy. The experimental results demonstrated the effectiveness and validity of the proposed strategy. The proposed strategy can be exploited to extend the spread of warnings or control the spread of rumors in social networks.

The influence of positive news on rumor spreading in social networks with scale-free characteristics

We explore the impact of positive news on rumor spreading in this paper. It is a fact that most of the rumors related to hot events or emergencies can be propagated rapidly on the hotbed of online social networks. In Chinese words, it is better to divert rather than block. Therefore, we propose the spreading model [Formula: see text] in which positive news is a good factor to guide rumor spreading. Based on transition probability method, we have got the spreading parameters of the [Formula: see text] model by running the rumor spreading process in online social networks with scale-free characteristics. The results give a good proof that improving the activity of the positive news spreader [Formula: see text] derived from the [Formula: see text] model can guide and restrain the spreading speed of rumor smoothly.

Active influence spreading in social networks

Identifying the most influential spreaders is an important issue for the study of the dynamics of information diffusion in complex networks. In this paper we analyze the following spreading model. Initially, a few nodes know a piece of information and are active spreaders of it. At subsequent rounds, spreaders communicate the information to their neighbors. Upon receiving the information, a node becomes aware of it but does not necessarily become a spreader; it starts spreading only if it gets the information from a sufficiently large number of its neighbors. A set of initial spreaders that guarantees that all the nodes become aware of the information is called a perfect seed set. We study the problem of choosing a perfect seed set of minimum size. We provide hardness results and show that the problem becomes tractable on trees. In case of general graphs, we provide an efficient algorithm and validate its effectiveness (in terms of the solution size) on real-life networks. We also study perfect seed sets in dense graphs and derive a bound on the size of a dominating set in Ore graphs.

Exploring the Identification and Effects of “Opinion Leader” under Different Information Release Strategies

This paper systematically analyzes the models and processes related to wordof- mouth spreading in social networks. This paper simulates the characteristics and rules of word-of-mouth spreading on social network platforms, adopts network evolution models as well as virus spreading models which can precisely reflect the process of word-of-mouth spreading. By computer simulation, the effect of several kinds of parameters in networks and in wordof- mouth spreading model is analyzed. What has been proved, through parameter analysis, is that the secondary “push” of the key node (opinion leader) in social networks has played a significant role in promoting word-of-mouth spreading. In practical applications, shopkeepers can act appropriately to the situation, which means they put in a second period of advertise appropriately after placing one advertisement at random in order to save costs and increase efficiency.

ФОТОГРАФІЯ ЯК ДОКАЗ НАШОГО ІСНУВАННЯ

Мета роботи. Це дослідження покликане доповнити загальну картину історії розвитку фотографії та її можливості впливати на реальність. Фотографія за своєю природою є технічним мистецтвом, але керує надзвичайно складною сучасною технікою людина. Питання «що таке сучасна фотографія?» набуває особливої актуальності в зв’язку з тим, що в XXI ст., завдяки введенню абсолютно нової техніки, виникає альтернативний розвиток фотографії. Методи дослідження. У статті прослідковується ланцюжок від появи перших фотографічних зображень до фотографій сьогодення. Особливу увагу було приділено розгляду ролі в культурі аматорської та побутової фотографії. Виявлено, що ці напрями фотографії доволі суттєво впливають на становище фотографічної справи як виду мистецтва. Аналізуючи зміст даних видів фотографії, було зазначено, що саме фотографії цих напрямків стають «дзеркалом реальності». Наукова новизна. Аналізуючи поведінку людини в сучасному культурному середовищі, можна зробити припущення, що людина, яка занурена у світ фотографічних образів, починає діяти та ідентифікувати себе як образ. Висновки. Намагаючись дослідити розвиток сучасної фотографії, неможливо чітко визначити її роль і розкрити механізми впливу фотографії на суспільство. Це пояснюється тим, що фотографія впливає на людину і культуру своїми власними шляхами, що призводить до неоднорідності формування реальності. Ще однією тенденцією є глибоке занурення фотографії в сферу Інтернет простору. Поширення соціальних мереж, блогів і сервісів мікроблогінгу дозволили фотографії стати засобом актуалізації віртуальної реальності або «реальної віртуальності» в просторі повсякденного життя.

Controlling percolation with limited resources.

Connectivity, or the lack thereof, is crucial for the function of many man-made systems, from financial and economic networks over epidemic spreading in social networks to technical infrastructure. Often, connections are deliberately established or removed to induce, maintain, or destroy global connectivity. Thus, there has been a great interest in understanding how to control percolation, the transition to large-scale connectivity. Previous work, however, studied control strategies assuming unlimited resources. Here, we depart from this unrealistic assumption and consider the effect of limited resources on the effectiveness of control. We show that, even for scarce resources, percolation can be controlled with an efficient intervention strategy. We derive such an efficient strategy and study its implications, revealing a discontinuous transition as an unintended side effect of optimal control.

Comparing Personality Traits, Mental Health and Self-Esteem in Users and Non-Users of Social Networks

Abstract Background: Various aspects of the psychological component have been affected by the spread of social networks and using these networks by the students. Objectives: This study aimed to examine the personality traits, mental health and self-esteem in users and non-users of social networks. Methods: This study conducted as a casual-comparative study among the descriptive designs. In this regard, 372 female high school students studying in the school year 2015 - 2016 were selected from the Instagram and Telegram users of the social networks using multi-stage cluster sampling. Self-made demographic information questionnaire for the participants, Rosenberg questionnaire for evaluating self-esteem index, Hegzako questionnaire for personality traits and Goldberg mental health questionnaire for mental health index were used in the study. Data were analyzed by chi-square, analysis of variance and Bonferroni test. Results: The results showed that there was a significant difference between users and non-users groups in terms of openness personality component (P < 0.05). Furthermore, there was a significant difference in four components of mental health (P < 0.01). There was also a significant difference for self-esteem index between two groups (P < 0.05). Conclusions: The findings of this study emphasize the attention to psychological factors in planning of preventive interventions.

Effects of rewiring strategies on information spreading in complex dynamic networks

Recent advances in networks and communication services have attracted much interest to understand information spreading in social networks. Consequently, numerous studies have been devoted to provide effective and accurate models for mimicking information spreading. However, knowledge on how to spread information faster and more widely remains a contentious issue. Yet, most existing works are based on static networks which limit the reality of dynamism of entities that participate in information spreading. Using the SIR epidemic model, this study explores and compares effects of two rewiring models (Fermi–Dirac and Linear functions) on information spreading in scale free and small world networks. Our results show that for all the rewiring strategies, the spreading influence replenishes with time but stabilizes in a steady state at later time-steps. This means that information spreading takes-off during the initial spreading steps, after which the spreading prevalence settles toward its equilibrium, with majority of the population having recovered and thus, no longer affecting the spreading. Meanwhile, rewiring strategy based on Fermi-Dirac distribution function in one way or another impedes the spreading process, however, the structure of the networks mimic the spreading, even with a low spreading rate. The worst case can be when the spreading rate is extremely small. The results emphasize that despite a big role of such networks in mimicking the spreading, the role of the parameters cannot be simply ignored. Apparently, the probability of giant degree neighbors being informed grows much faster with the rewiring strategy of linear function compared to that of Fermi-Dirac distribution function. Clearly, rewiring model based on linear function generates the fastest spreading across the networks. Therefore, if we are interested in speeding up the spreading process in stochastic modeling, linear function may play a pivotal role.

User-Generated Services Composition in Smart Multi-User Environments

The increasing complexity shown in Smart Environments, together with the spread of social networks, is increasingly moving the role of users from simple information and services consumers to actual producers. In this work, we focus on security issues raised by a particular kind of services: those generated by users. User-Generated Services (UGSs) are characterized by a set of features that distinguish them from conventional services. To cope with UGS security problems, we introduce three different policy management models, analyzing benefits and drawbacks of each approach. Finally, we propose a cloud-based solution that enables the composition of multiple UGSs and policy models, allowing users’ devices to share features and services in Internet of Things (IoT) based scenarios.

Modeling and inferring mobile phone users’ negative emotion spreading in social networks

Individual emotion, as an important part of personal privacy on health information, is vital for physical and emotional well-being. Despite the physiological reasons, emotion contagion between peoples is pivotal to understand people’s emotional changes. However, most existing works at the individual level focus on small groups in the short term. Because negative emotions are natural to appear and can largely affect the dynamics of emotion spreading, therefore this paper aims to investigate the negative emotion spreading mechanism at the individual level of large user groups in the long term, and finally infer individuals’ ability of the negative emotion spreading by observing people’s behaviors on mobile social networking. Specifically, we first propose a novel metric for measuring individuals’ degree of negative emotion spreading. We then put forward a Graph-Coupled Hidden Markov Sentiment Model for modeling the propagation of infectious negative sentiment locally within a social network using data collected by mobile phones. In this model, we assume that one can infect others even if he/she is not infected, which is an extension of the traditional assumption in epidemic spreading. Because the proposed model involves parameters, to infer those parameters, Gibbs sampling method is employed. Experiments on both synthetic and real-world network datasets are carried out, and the efficacy of our proposed model is verified. The case study on real-world, as a potential application, demonstrates that the proposed model provides a useful insight for understanding the correlation between network structure and the emotion shift.

Epidemic spreading over quenched networks with local behavioral response

We discuss the impact of local information-based behavioral response on epidemic spreading in social networks. By using a pair quenched mean-field approach developed by Mata and Ferreira [Europhys. Lett. 103 (2013) 48003], we derive a dynamical model governing the epidemic spreading over a random network with a linear response function and density-dependent epidemic information. A deterministic relation between the epidemic threshold and the response parameter is derived according to a quasi-static approximation method. It is found that local behavioral response will induce the extinction of the disease via rasing the epidemic threshold. Additionally, the theoretical result is supported by stochastic simulations on an Erdo¨s–Rényi random network and a Baraba´si–Albert scale-free network. Simulations show that the pair quenched mean-field approach is more accurate than the classical quenched mean-field approach.

Accounting Information Systems in an Open Society. Emerging Trends and Issues

During the second decade of the XXI Century, several contextual forces have changed the way in which firms interact with environment. The economic and financial crisis, the development of technologies, the convergence between different communication channels and the spread of social networks are just some of the forces that determine a quick and radical change in the way employees and firms look at the future and interact each other. This contribution focuses on the meaning of the word as one of the keywords of this period and highlights how the open society affects accounting information systems, as systems processing information to support strategic decisions in such a complicated environment.

Effects of time-dependent diffusion behaviors on the rumor spreading in social networks

When considering roles of realistic external forces (e.g. authorities) and internal forces (e.g. the forgetting nature of human), diffusion behaviors like spreading, stifling and forgetting behaviors are time-dependent. They were incorporated in an SIR-like rumor spreading model to investigate the effects to rumor spreading dynamics. Mean-field equations were derived, and the steady state analysis was conducted. Simulations were carried out on different complex networks. We demonstrated that the combination of the three variable diffusion behaviors provides a faster and larger spreading expansion capacity. Network structure matters considerably in rumor spreading dynamics.

MapReduce-based efficient betweenness approximation pivot method for large graphs

The important person is vital for information spreading efficiency in social networks, which has always been the hottest research field in recent years. Nowadays, with the increased information spreading speed in our daily life such as cellphone or microblog, the government and enterprise have realised that it is necessary and important to manage and control the information spreading in social networks of people by recognising the important person or VIP customer. Meanwhile, with the rapid increase of information in society activities recently, the distributed information system engineering such as MapReduce-based computation system has become more and more popular in large-scale social network data analysis in emergency case management or VIP customer recognition. In this article, a novel effective and efficient node betweenness approximation pivot selection method for largescale graphs is proposed based on MapReduce-based system for social network analysis SNA. Furthermore, it has been proved useful in four discrete datasets and one continuous dataset six month cellphone call graph in VIP customer discovery for large graphs from real telecom data in China to help deal with customer relationship management more efficiently.

Cognitive Architecture of Collective Intelligence Based on Social Evidence

Development of collective intelligence and consciousness starts playing key evolutionary role given spread of social networks and massive Internet communications. Paper considers cognitive model and architecture capable to capture cognitive phenomena in social environments, which could be used for modeling of collective cognition as well as developing practical applications for individual interaction with collective intelligence. The model is evaluated by means of qualitative and quantitative experiments.

Hábitos de uso en las Redes Sociales de los y las adolescentes: análisis de género

El impacto provocado por la generalización de las Redes Sociales ha supuesto drásticas transformaciones en las formas de comunicación y socialización. Esta realidad no deja al margen a los/las adolescentes, verdaderos/as nativos/as digitales. El objetivo de este estudio consiste en conocer los hábitos de uso en las Redes Sociales de los/as estudiantes ourensanos/as analizando las diferencias de género. La muestra estaba formada por 1283 estudiantes de la provincia de Ourense con una media de edad de 15,55 (DT: 1,6). Entre las conclusiones más relevantes se destaca que las R.S. son utilizadas tanto por chicos como por chicas con asiduidad. La mayor parte de los/as adolescentes refieren tener perfiles en una o más R.S. (siendo Facebook, Twitter y Tuenti las más utilizadas), a las que acceden fundamentalmente a través de su móvil (Chi2= 5,86; p&lt;.05) tanto chicas (88.1%) como chicos (83.3%). Se revelan cifras similares en lo relativo al número de contactos agregados en Facebook y Tuenti (entre 100 y 300 contactos mayoritariamente). No obstante tanto en Twitter (Chi2=40.1; p&lt;.001) como en Instagram (Chi2=43.7; p&lt;.001) las chicas manifiestan tener más contactos que sus compañeros, entre 500 (17.5%) y más de 1000 (22.5%). Son también las chicas (27.7%) las que conceden mayor importancia al número de contactos frente a los chicos (25.2%). No obstante solamente un 4.5% de ellas afirma que siempre aceptan las solicitudes de amistad aunque no sepan quién es la otra persona (Chi2=14,53; p&lt;.01) frente al 9.8% de ellos que así lo afirma. Algunos/as de los chicos (46.5%) y las chicas (41.6%) que etiquetan a contactos en fotos consideran que hacerlo los hace más populares (23.2% chicos y 18.8% chicas). Las chicas son más cuidadosas en la privacidad de sus perfiles teniendo en mayor medida perfiles cerrados/protegidos, el 66.2% de las chicas declara que solo sus amistades pueden ver sus perfiles frente al 56.1% de los chicos que así lo manifiesta (Chi2=13.61; p&lt;.01). En esta línea el 22.3% de los chicos frente al 17.9% de las chicas tienen perfiles que pueden ser observados por cualquier persona conocida y/o desconocida. Son ellas las que tienen mayor conciencia sobre el peligro de las R.S, afirmando que su uso puede llegar a ser “peligroso” o “muy peligroso” en el 44.2% de los casos frente al 35.1% de los chicos que así lo afirma (Chi2=23.26; p&lt;.001). Asimismo son ellas las que afirman en mayor medida que sus amigos/as consideran el uso de las R.S peligroso (48.3% de chicos y un 52.7% de chicas). A pesar de que tanto los chicos (91.4%) como las chicas (86.2%) no son supervisados sobre el acceso/uso a las R.S, son ellas las que recibir más vigilancia (Chi2=8.44; p&lt;.01). Los chicos (33%) afirman más que sus compañeras (23.4%) que nunca han recibido formación sobre el uso de las R.S (Chi2=14,32; p&lt;.001). A la vista de los resultados obtenidos se pone de manifiesto la necesidad de formación sobre el uso responsable de las redes sociales por parte de los y las adolescentes así como de docentes y familias.