646 resultados para Twitter, social networks, public opinion, agenda setting, Álvaro Uribe Vélez
Resumo:
Campaigners are increasingly using online social networking platforms for promoting products, ideas and information. A popular method of promoting a product or even an idea is incentivizing individuals to evangelize the idea vigorously by providing them with referral rewards in the form of discounts, cash backs, or social recognition. Due to budget constraints on scarce resources such as money and manpower, it may not be possible to provide incentives for the entire population, and hence incentives need to be allocated judiciously to appropriate individuals for ensuring the highest possible outreach size. We aim to do the same by formulating and solving an optimization problem using percolation theory. In particular, we compute the set of individuals that are provided incentives for minimizing the expected cost while ensuring a given outreach size. We also solve the problem of computing the set of individuals to be incentivized for maximizing the outreach size for given cost budget. The optimization problem turns out to be non trivial; it involves quantities that need to be computed by numerically solving a fixed point equation. Our primary contribution is, that for a fairly general cost structure, we show that the optimization problems can be solved by solving a simple linear program. We believe that our approach of using percolation theory to formulate an optimization problem is the first of its kind. (C) 2016 Elsevier B.V. All rights reserved.
Resumo:
Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Resumo:
How can networking affect the turnout in an election? We present a simple model to explain turnout as a result of a dynamic process of formation of the intention to vote within Erdös-Renyi random networks. Citizens have fixed preferences for one of two parties and are embedded in a given social network. They decide whether or not to vote on the basis of the attitude of their immediate contacts. They may simply follow the behavior of the majority (followers) or make an adaptive local calculus of voting (Downsian behavior). So they either have the intention of voting when the majority of their neighbors are willing to vote too, or they vote when they perceive in their social neighborhood that elections are "close". We study the long run average turnout, interpreted as the actual turnout observed in an election. Depending on the combination of values of the two key parameters, the average connectivity and the probability of behaving as a follower or in a Downsian fashion, the system exhibits monostability (zero turnout), bistability (zero turnout and either moderate or high turnout) or tristability (zero, moderate and high turnout). This means, in particular, that for a wide range of values of both parameters, we obtain realistic turnout rates, i.e. between 50% and 90%.
Resumo:
We provide empirical evidence to support the claims that social diversity promotes prosocial behavior. We elicit a real-life social network and its members’ adherence to a social norm, namely inequity aversion. The data reveal a positive relationship between subjects’ prosociality and several measures of centrality. This result is in line with the theoretical literature that relates the evolution of social norms to the structure of social interactions and argues that central individuals are crucial for the emergence of prosocial behavior.
Resumo:
Nowadays, enterprises, and especially SMEs, are immersed in a very difficult economic situation. Therefore, they need new and innovative tools to compete in that environment. Integration of the internet 2.0 and social networks in marketing strategies of companies could be the key to success. If social networks are well managed, they can bring a lot to enterprise plans. Moreover, social networks are very attractive from an economic point of view as companies can find most of their customers on it.
Resumo:
This study explored the factors associated with state-level allocations to tobacco-control programs. The primary research question was whether public sentiment regarding tobacco control was a significant factor in the states' 2001 budget decisions. In addition to public opinion, several additional political and economic measures were considered. Significant associations were found between our outcome, state-level tobacco-control funding per capita, and key variables of interest including public opinion, amount of tobacco settlement received, the party affiliation of the governor, the state's smoking rate, excise tax revenue received, and whether the state was a major producer of tobacco. The findings from this study supported our hypothesis that states with citizens who favor more restrictive indoor air policies allocate more to tobacco control. Effective public education to change public opinion and the cultural norms surrounding smoking may affect political decisions and, in turn, increase funding for crucial public health programs.
Resumo:
The development of the Internet and in particular of social networks has supposedly given a new view to the different aspects that surround human behavior. It includes those associated with addictions, but specifically the ones that have to do with technologies. Following a correlational descriptive design we present the results of a study, which involved university students from Social and Legal Sciences as participants, about their addiction to the Internet and in particular to social networks. The sample was conformed of 373 participants from the cities of Granada, Sevilla, Málaga, and Córdoba. To gather the data a questionnaire that was design by Young was translated to Spanish. The main research objective was to determine if university students could be considered social network addicts. The most prominent result was that the participants don’t consider themselves to be addicted to the Internet or to social networks; in particular women reflected a major distance from the social networks. It’s important to know that the results differ from those found in the literature review, which opens the question, are the participants in a phase of denial towards the addiction?
Resumo:
In this article, we address the importance and relevance that social networks exhibit in their use as an educational resource. This relevance relies in the possibility of implementing new learning resources or increasing the level of the participant's connectivity, as well as developing learning communities. Also, the risk entailed from their use is discussed, especially for the students that have a low technological education or those having excessive confidence on the media. It is important to highlight that the educational use of social networks is not a simple extension or translation of the student's habitual, recreational use, but that it implies an important change in the roles given to teachers as well as learners; from accommodative learning environments that only encourage memorization to other environments that demand an active, reflective, collaborative and proactive attitude, that require the development/acquisition of technological as well as social abilities, aptitudes and values. It is also important to highlight that a correct implementation and adequate use will not only foment formal learning, but also informal and non-formal learning.