who opposes Crito’s attempt to save him in part because of his belief in following ones’ conscience over the concerns of the majority, is a supporter of the status quo and has, as such, lent support to the use of law not as a force for justice but as a socialmechanism for control. One wonders if Plato portrayed Socrates as he did for political reasons. It is crucial to keep in mind that Plato wrote the dialogue, not Socrates. Crito is Plato’s dramatization of what might or might not have transpired. It has been said that Xenophon gives an entirely different account of Socrates’ trial than Plato. According to his account, Socrates never spoke in his own defense. So, we have reason to wonder about the veracity of Plato’s account. Given the fact that Socrates had been condemned to death for political reasons, if that was the case, Plato may have thought it wise to present his master as a supporter of the state rather than as a rebel. In this way, he may well have been protecting himself and his Academy. Clearly, we can only speculate about this, but it does seem strange that a man who has been unjustly convicted by a group of people whose political views he does not appear to share would be dedicated to the perpetuation of their hegemony. If my speculation concerning Plato is true, then we are presented with yet another example of how law or, in this case, a renowned philosophical doctrine concerning law and obedience, has been uses as a socialmechanism for control.
Yu and Singh  present a referral system for agents that enables them to share referrals for the location of relevant information. Finding relevant information involves finding the right information sources, for instance, the people or agents to ask, who have the desired information or expertise. The social network is important in discovering those relevant sources. Due to issues such as privacy, agents will not list their social relationships on a central repository. Agents can, however, gather this information through distributed searches through referrals. Focussing on the dynamics of social networks and their effects in information flow, Yu and Singh seek to efficiently search social networks with the help of agents and their local knowledge. Each agent maintains a personal social network and queries other agents for information and these agents may respond with a reply or with referrals to others. An agent’s personal social network models its acquaintances, the closest ones are known as neighbours. As it is only allowed a small number of neighbours, the agent periodically reviews its acquaintances and may promote or demote some of them. This process is based on the answers to queries and the expertise of the referring agent.
The presence of inactive or ‘ lazy ’ workers has received some attention in social insects (Dornhaus et al., 2008; Beshers and Fewell, 2001) and may be accounted for proximately by task thresholds, as inactive individuals are likely to be those that require a higher level of stimulus before they engage in a given task (Robinson et al., 2009). However, here we see a case of active but ineffective workers in a task that is moderately difficult to complete (only 65% of all tandem runs were successful). While the exact mechanisms underlying this are as yet unknown, there are several potential causes. One possibility is that workers attempting a greater number of tandem runs were doing so as a compensatory reaction to failing more often. This is plausible, as interruptions to tandem runs were common in our experiment, as in others (Franks et al., 2009). It is also likely that highly active individuals made a significant contribution by leading only partially successful tandem runs. This is because, as demonstrated in previous experiments (Franks et al., 2010), even when tandem runs end prematurely, they may still be effective in directing naive workers to a new nest (Franks et al., 2010; Pratt, 2008). However, while both of these factors provide viable explanations, their relative importance will probably require further investigation.
Burd (1993) defines that “The socialmechanism is a stable in the sense of form social relations, which is realized with any number of repetitions with a maximally predictable result. The realization of social action in the form of a socialmechanism presupposes an orientation toward the other people behavior; that is on the contact of the individual with the sociocultural environment. The function of the socialmechanism is to secure the "correct" actions, or rather, what is considered correct in each social environment. In the case of material and production activities, mistakes are punished by the nature. In social activity, other members of society make their judgments about the actions of the individual. Since any social action presupposes a definite conscious need, motivation and purpose, the subjective basis of behavior is realized in the socialmechanism considering the cultural norms of this society. The objective basis of behavior is how effective the information, energy, and matter are exchanged with the help of this socialmechanism. Individual personality qualities that are in demand in the process of evolutionary development are cognitive complexity of thinking, high variability of behavior and the nature of the setting. Their maximum quality is found in representatives of the elite.”
In this work, in order to give a new algorithm for the Influence Maximization problem, that keeps into consideration the history of actions that have been taken by the users in determining their influence over each other. Also, it uses the concept of community detection and its relationship with the field of Viral Marketing. I propose that instead of the Social Marketing & Influence model which has been used to simulate propagation of influence. In this work, in order to give a new algorithm for the Influence Maximization problem, that keeps into consideration the history of actions that have been taken by the users in determining their influence over each other. Also, it uses the concept of community detection and its relationship with the field of Viral Marketing. I propose that instead of the Social Marketing & Influence model which has been used to simulate propagation of influence. Now, to use this scanning of action log to determine probabilistic influence between any two users. Once we have these influence values we will apply topic aware influence maximization framework along with linear threshold model so that performance and influence result should get improved, with probability values that are actually significant. This approach is clearly more practical and hence more accurate than assigning random probability values to each of these edges.
The buying and selling and sharing records are tested in cloud with particular cloud suppliers and that they supply severa establishments. Inbound ambushes concentrating on the cloud can reason splendid and great, accidental deferred final outcomes. A propelling exam of server farm chiefs presentations that 1/2 of of them experienced DDoS actions, with ninety four% of these experiencing regular assaults. Jagatic et al., (2007) exhibited a social phishing concept with its distinctive consequences. It's miles pointed out with the virtual life seems like fb or Tweeter.It takes after the assault that have to be tended to with the arranged facts and provide get right of access to to unique man or woman statistics. As an instance, a phisher harming himself as a monster keeping cash alliance or no ifs, ands or buts understood on-line closeout web site could have an low priced yield, paying little persona to spotting little to not anything about the recipient.
Abstract: The internet has a considerable effect on social relations and connections among people. Social networking platforms have been an enormous medium for establishing relations and connections among different people all over the world. People, organizations and companies use these platforms to communicate and interact with their communities and audience. These platforms have made it easy for people to share information, create content, and communicate and connect with others online; however, online interaction and communication among people have resulted in the creation of many problems. Malicious contents can easily be shared and populated to reach a wider audience than by using the traditional sharing methods. Detection mechanism is a growing area of research that can detect any inappropriateness of data that is more sensitive to malicious behavior. The detection mechanism needs to be involved in the analysis of the abusing messages posted on the Twitter account of King Saud University (KSU). Text mining is one approach that can be used to detect such malicious or abusing messages. Text mining techniques provide the means to perform data classification where messages can be classified into malicious and non-malicious messages. In addition, Sentiment Analysis is used to identify user tendencies, trends, and opinions by classifying a text into positive, negative and neutral. In this paper, we aim to provide a literature review to investigate the current techniques. The study also addresses the detection of malicious messages which identifies the behavior of malicious and abusive messages. Based on the extensive review of the current techniques, our focus is on the analysis of Arabic and English tweets on KSU’s Twitter account. First, data was collected from Twitter. This was followed by the preprocessing phase. Then, a corpus was produced applying a machine learning based approach by using Naive Bayes and Random Forest Classifier algorithms. Subsequently, the study focused on comparing the accuracy and performance of the Naive Bayes classifier with Random Forest Classifier algorithms in analyzing Arabic and English texts. In order to ensure reaching accurate results, Arabic and English tweets were analyzed.
From the industrial characteristics, the forestry industry is a covering a wide range of industrial chain length, product variety and more complex industrial groups, is an important part of the national economy. Forestry industry not only pro- vides a lot of material and non-material products, including wood, bamboo, ply- wood, wood pulp, forest products, wood grain, flowers, herbs, forest food, forest and tourism for national development and people’s lives, but also to promote rural industrial restructuring, to solve the mountainous areas of farmers out of poverty, to provide social employment opportunities, and so has an extremely important role. From the production technology features industry perspective, the forestry industry is the land as the basic means of production forest (includ- ing natural forests and plantation) as the main use of objects throughout the production process including 3 composition sections: forestation, forest man- agement, forest use. From the property development business’ point of view, since 1998 China Natural Forest Protection Project started, the forest in China is divided into two categories: ecological forest and commercial forest. Ecological public welfare forest is of great importance to the ecological location, or ex- tremely fragile ecological conditions, and plays an important role in ecological security, biodiversity conservation and economic and social sustainable devel- opment. It provides forest ecological and social service products as the main business purpose. According to the power level can be divided into national public welfare forest and local public welfare forest. Commercial forest play is based on the economic benefits based forest to produce timber, fuel-wood, fresh and dried products and other industrial raw materials such as the main purpose of the for- est, forest, including timber, economic forests and firewood.
1. We study social influence from a topic modeling perspective. We introduce novel topic-aware influence-driven propagation models that experimentally result to be more accurate in describing real-world cascades than the standard propagation models studied in the literature. 2. In particular, we first propose simple topic-aware extensions of the well-known Independent Cascade and Linear Threshold models. Next, we propose a different approach explicitly modeling authoritativeness, influence and relevance under a topic-aware perspective.
Ultimately, we hoped to tease apart the two explanations of social tuning. If the shared reality interpretation was more accurate, then the measure of implicit
personalized attitudes should show the same decrease in implicit prejudice that the implicit prejudice measure would. For example, when interacting with the likable experimenter with egalitarian views, participants would display less prejudice on the implicit prejudice measure as well as the personalized implicit prejudice measure, when compared to individuals who interacted with the dislikable experimenter, or those low in affiliative motivation. We did not see this effect either. If the social norms support was accurate, we expected to see a main effect of perceived beliefs. Specifically,
This paper used Sina microblog which is the most mature data source to collect the public opinion about “The man who insulted the murder’s mother was killed” case as sample data, and analyse the spread of public opinion among the whole network, individual network, subgroup network with social network analysis method and UCINET. From the perspective of the spread of public opinion among the whole network, the overall network density measure shows that the network's ability to receive and control information is directly influenced by where there is a strong link between the conveyors. Under this construction, if we want to control the circulating speed of the Internet public opinion, as long as we control key nodes, so as to control the situation of circulating of Internet public opinion. As for individual network, this paper used structural hole theory to study it. The results show that we have to control the amount of structural holes among conveyors to control the circulating of Internet public opinion. Since the number of conveyors in social network is very extensive, so controlling the structural holes between key conveyors is enough to control the direction and range of the circulation of Internet public opinion. As for subgroup network, nodes that play the role of connecting each subgroup are important for information exchange. In the process of Internet public public circulation, an individual group is far from enough. It’s the circulation and communication between groups that count, and by controlling which we can control the spread of Internet public opinion.
Undertaking social responsibility is a good driving force for the sustained and healthy growth of an enterprise. Social responsibility is far from a cost, a constraint condition, or a charitable act, but a source and motive force for the development of opportunities, innovative competition and benign growth . Oil and gas enterprises have recognized this issue and started to pay attention to social responsibility construction, but these efforts have not played a due role because of two reasons below. First, these measures separate the social responsibility of oil and gas enterprises against the profitability of oil and gas enterprises, ignoring the interdependence between the two. Second, when considering the social responsibility, the oil and gas enterprises have not combined it with the business strategy of the enterprises and taken it into the track of long-term development of the oil and gas enterprises, but only for social responsibility itself. In fact, the approaches that many oil and gas companies use to cope with social responsibility are neither systematic nor long-term. Oil and gas enterprises are an integral part of the social environment system, and are closely related to the social environment. If oil and gas enterprises want to survive and develop, they must adapt to this environment. The survival of the fittest is a universal law. Therefore, it’s necessary for oil and gas enterprises to make a benign response to the society and bear social responsibility, and then, what’s the social power source? What is the relationship between the power source and the improvement of social responsibility? If we find out the power source and optimize its operating mechanism, we can improve the social responsibility and enhance the power of sustainable development of oil and gas enterprises.
the probability that worker i gets the job offer with wage w > 0. Recall that the firm does not know the exact productivity types of two workers, but its aim is to hire a worker with productivity as high as possible. This aim can be represented by a social choice function f (⃗θ) = (y 1 (⃗θ), y 2 (⃗θ)), in which
The BPM Company starts a new recruitment of the year. Difference from the past, the company decides to do the talents-hunter job on the Internet in this year. That is, the recruitment advertisement and application collection are all finished based on the social media. The managers of HR sector are responsible for the recruitment plan and requirement. All the other colleagues of HR sector are all responsible for posting the recruitment ads on social network platforms where they are registered. With all of the applications each HR receives and then are handed on to the HR manager, a screening procedure will be performed by the manager based on the applicant’s resumes and the position requirements. The applications passing the first round screening will be replied with the offer of the opportunity of second-round interview. Otherwise they will be replied with a rejection letter. Then the process of the talents-huntering job is finished.
test of the full mediation model was conducted, to determine whether the path coefficient for the relationships between social cohesion and well-being were equal in both groups (ie, older men and women). Using SPSS Amos software, the mul- tigroup option was employed, to determine any significant differences in structural parameters between older males and older females. The first step of the analysis involved test ing the baseline model for the two groups. Therefore, the vali- dated structural path model was examined across two groups (older men and women) considered collectively – without any equality-constrained relationship across two groups. Figure 3 and Figure 4 show the tested model, indicating good fit between the data and the model ( c 2 = 383.21; P0.001;
of total endowment of social capital. 15 For example, a household may be endowed with only one measure of social capital, while others may be endowed with more, and even all, measures. Comparing the estimates across different groups, one can understand the effects of different intensities of social capital. To proceed, we first sum all three binary measures of social capital to construct an “Aggregate” measure. This measure ranges between 0 (no social capital) and 3 (maximum). Second, we create four dummies from this “Aggregate” measure—i) households with no social capital, ii) households with any one component of social capital, iii) households with any two components of social capital, and iv) households with all three components of social capital. We include the last three dummies (households with no social capital as the base category) in the regression to compare whether larger endowment of social capital has incremental effects. Finally, we construct a dummy indicating whether a household is endowed with any social capital (1 if at least one of help, invitation, or shalish is “yes”; 0 otherwise), which we refer to as a “Binary Aggregate.”
The rumor spreading has been widely studied by scholars. However, there exist some people who will persuade infected individuals to resist and counterattack the rumor propagation in our social life. In this paper, a new SICS (susceptible-infected-counter-susceptible) rumor spreading model with counter mechanism on complex social networks is presented. Using the mean-field theory the spreading dynamics of the rumor is studied in detail. We obtain the basic reproductive number ρ and equilibriums. The basic reproductive number is correlated to the network topology and the influence of the counter mechanism. When ρ < 1 , the rumor-free equilibrium is globally asymp- totically stable, and when ρ > 1 , the positive equilibrium is permanent. Some interesting patterns of rumor spreading involved with counter force have been revealed. Finally, numerical simula- tions have been given to demonstrate the effectiveness of the theoretical analysis.