• Title/Summary/Keyword: social networks

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Impact of Human Mobility on Social Networks

  • Wang, Dashun;Song, Chaoming
    • Journal of Communications and Networks
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    • v.17 no.2
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    • pp.100-109
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    • 2015
  • Mobile phone carriers face challenges from three synergistic dimensions: Wireless, social, and mobile. Despite significant advances that have been made about social networks and human mobility, respectively, our knowledge about the interplay between two layers remains largely limited, partly due to the difficulty in obtaining large-scale datasets that could offer at the same time social and mobile information across a substantial population over an extended period of time. In this paper, we take advantage of a massive, longitudinal mobile phone dataset that consists of human mobility and social network information simultaneously, allowing us to explore the impact of human mobility patterns on the underlying social network. We find that human mobility plays an important role in shaping both local and global structural properties of social network. In contrast to the lack of scale in social networks and human movements, we discovered a characteristic distance in physical space between 10 and 20 km that impacts both local clustering and modular structure in social network. We also find a surprising distinction in trajectory overlap that segments social ties into two categories. Our results are of fundamental relevance to quantitative studies of human behavior, and could serve as the basis of anchoring potential theoretical models of human behavior and building and developing new applications using social and mobile technologies.

Attachment Styles and Social Networks of Mothers of School Children (학동기 자녀를 둔 어머니의 애착양식과 사회관계망)

  • 유계숙
    • Journal of Families and Better Life
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    • v.17 no.2
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    • pp.43-54
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    • 1999
  • This study examined the impact of attachment styles on the size and the level of functions of social networks. 270 mothers of school children responded to the questionnaire and were classified into secure avoidant and anxious attachment groups. Findings indicated that three continuous attachment indexes security avoidance anxiousness and the size and the level of functions of social networks were not affected by mother's age educational level and employment status. However singnificant attachment style effects were obtained for the size and the level of functions of social networks. Secure subjects perceived their husbands closer and more important and listed more nonkin members in their netoworks than anxious subjects. important and listed more nonkin members in their networks than anxious subjects Also secure people perceived receiving more assistance from network members including household tasks money information and advice Secure and anxious subjects reported more emotio al support from networks than avoidant people.

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Unsupervised Scheme for Reverse Social Engineering Detection in Online Social Networks (온라인 소셜 네트워크에서 역 사회공학 탐지를 위한 비지도학습 기법)

  • Oh, Hayoung
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.3
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    • pp.129-134
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    • 2015
  • Since automatic social engineering based spam attacks induce for users to click or receive the short message service (SMS), e-mail, site address and make a relationship with an unknown friend, it is very easy for them to active in online social networks. The previous spam detection schemes only apply manual filtering of the system managers or labeling classifications regardless of the features of social networks. In this paper, we propose the spam detection metric after reflecting on a couple of features of social networks followed by analysis of real social network data set, Twitter spam. In addition, we provide the online social networks based unsupervised scheme for automated social engineering spam with self organizing map (SOM). Through the performance evaluation, we show the detection accuracy up to 90% and the possibility of real time training for the spam detection without the manager.

An Uncertain Graph Method Based on Node Random Response to Preserve Link Privacy of Social Networks

  • Jun Yan;Jiawang Chen;Yihui Zhou;Zhenqiang Wu;Laifeng Lu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.1
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    • pp.147-169
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    • 2024
  • In pace with the development of network technology at lightning speed, social networks have been extensively applied in our lives. However, as social networks retain a large number of users' sensitive information, the openness of this information makes social networks vulnerable to attacks by malicious attackers. To preserve the link privacy of individuals in social networks, an uncertain graph method based on node random response is devised, which satisfies differential privacy while maintaining expected data utility. In this method, to achieve privacy preserving, the random response is applied on nodes to achieve edge modification on an original graph and node differential privacy is introduced to inject uncertainty on the edges. Simultaneously, to keep data utility, a divide and conquer strategy is adopted to decompose the original graph into many sub-graphs and each sub-graph is dealt with separately. In particular, only some larger sub-graphs selected by the exponent mechanism are modified, which further reduces the perturbation to the original graph. The presented method is proven to satisfy differential privacy. The performances of experiments demonstrate that this uncertain graph method can effectively provide a strict privacy guarantee and maintain data utility.

Social Incentives for Cooperative Spectrum Sensing in Distributed Cognitive Radio Networks

  • Feng, Jingyu;Lu, Guangyue;Min, Xiangcen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.2
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    • pp.355-370
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    • 2014
  • Cooperative spectrum sensing has been considered as a promising approach to improve the sensing performance in distributed cognitive radio networks. However, there may exist some selfish secondary users (SUs) who are unwilling to cooperate. The presence of selfish SUs could cause catastrophic damage to the performance of cooperative spectrum sensing. Following the social perspective, we propose a Social Tie-based Incentive Scheme (STIS) to deal with the selfish problem for cooperative spectrum sensing in distributed cognitive radio networks. This scheme inspires SUs to contribute sensing information for the SUs who have social tie but not others, and such willingness varies with the strength of social tie value. The evaluation of each SU's social tie derives from its contribution for others. Finally, simulation results validate the effectiveness of the proposed scheme.

Quantifying Influence in Social Networks and News Media

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.10 no.2
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    • pp.135-140
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    • 2012
  • Massive numbers of users of social networks share various types of information such as opinions, news, and ideas in real time. As a new form of social network, Twitter is a particularly useful information source. Studying influence can help us better understand the role of social networks. The popularity of social networks like Twitter is primarily measured by the number of followers. The number of followers in Twitter and the number of users exposed to news media are important factors in measuring influence. We chose Twitter and the New York Times as representative media to analyze the influence and present an empirical analysis of these datasets. When the correlation between the number of followers in Twitter and the number of users exposed to the New York Times is computed, the result is moderately high. The correlation between the number of users exposed to the New York Times and the number of sections including the users on it, was found to be very high. We measure the normalized influence score using our proposed expression based on the two correlation coefficients.

The First Stage of Developing the Adolescent Friendship Social Capital Scale

  • Xu, Leilei
    • Child Studies in Asia-Pacific Contexts
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    • v.2 no.1
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    • pp.29-43
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    • 2012
  • The purpose of the study was to generate the candidate items for the Adolescent Friendship Social Capital Scale. Both inductive and deductive approaches were used to generate the scale items. Halpern's conceptual map of social capital served as the theoretical basis of this scale, and guided the development of items. Semi-structured interviews with adolescents in Sydney, Melbourne and Beijing generated the initial pool of scale items. Twenty-six items were generated for the Adolescent Friendship Social Capital Scale. The items are organised in four theoretical constructs: Bonding Networks, Bridging Norms, Bridging Sanctions, and Linking Networks. Each item is a short statement followed by a five-point Likert scale anchored by 1= "Strongly disagree" and 5= "Strongly agree". The scale has several advantages over previous measures of adolescent friendship networks and friendship social capital. The scale has a strong and clear theoretical structure, the scale items demonstrate initial construct and content validity, and the format of the scale enables the collection of continuous data. However, in order to ensure the validity and reliability of the scale, another two stages of research need to be conducted in the future: scale development and scale evaluation.

Design of Query Processing System to Retrieve Information from Social Network using NLP

  • Virmani, Charu;Juneja, Dimple;Pillai, Anuradha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1168-1188
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    • 2018
  • Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

Features and Tendencies of the Digital Marketing Use in the Activation of the International Business Activity

  • Zhygalkevych, Zhanna;Zalizniuk, Viktoriia;Smerichevskyi, Serhii;Zabashtanska, Tetiana;Zatsarynin, Serhii;Tulchynskiy, Rostislav
    • International Journal of Computer Science & Network Security
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    • v.22 no.1
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    • pp.77-84
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    • 2022
  • The study highlights the features and trends of digital marketing for international business. To achieve these goals, the authors used a systematic approach that allows a comprehensive approach to the object of study, as well as used general and specific methods of scientific knowledge on the application of digital marketing for international business. The dynamics of the number of users of social networks in the world is analyzed, which allowed us to conclude about the steady trend of increasing the number of users of the Internet and social networks, as well as the time spent by users on social networks. The study of the dynamics of the number of users of social networks provides increased efficiency in the use of digital marketing tools to enhance international business. The most effective digital marketing tools for international business, including artificial intelligence, conversational marketing, chatbots, personalization, video marketing, live shopping, social media stories, interactive content, omnic marketing, augmented reality and technology immersion, native advertising, green marketing and mobile commerce.

Maternal Support Networks, Perceptions of Parenting Difficulty, and Children's Development (어머니의 사회적 관계망, 자녀양육에 대한 난이도 지각과 아동의 발달)

  • 이은해
    • Journal of the Korean Home Economics Association
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    • v.35 no.3
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    • pp.31-45
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    • 1997
  • The main purpose of the study was to examine relationships of child development with maternal social networks and maternal perceptions of parenting difficulty. Subjects were 90 children, ages 4 and 5, with their mothers. Child development was measured by School Readiness Test, peer nomination, and social competency ratings by teachers. Mothers responded to a questionnaire regarding social networks and parenting difficulty. The major findings of the study include: 1) Employed mothers reported receiving less emotional support and listed more in-laws and work colleagues in their social network than unemloyed mothers. 2) Mothers who perceived receiving more emotional support from networks reported less difficulty in parenting, especially in providing cognitive stimulation and daily routine care to their children. 3) Children's age and maternal perceptions of easiness in providing cognitive stimulation were the most contributing factors for predicting children's learning readiness and social competency.

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