scholarly journals Multi-Winner Contests for Strategic Diffusion in Social Networks

2019 ◽  
Vol 33 ◽  
pp. 6154-6162 ◽  
Author(s):  
Wen Shen ◽  
Yang Feng ◽  
Cristina V. Lopes
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Real World ◽  
Numerical Experiments ◽  
Budget Constraint ◽  
Individual Rationality ◽  
Proper Design ◽  
Reward Mechanisms ◽  
The Way

Strategic diffusion encourages participants to take active roles in promoting stakeholders’ agendas by rewarding successful referrals. As social media continues to transform the way people communicate, strategic diffusion has become a powerful tool for stakeholders to influence people’s decisions or behaviors for desired objectives. Existing reward mechanisms for strategic diffusion are usually either vulnerable to falsename attacks or not individually rational for participants that have made successful referrals. Here, we introduce a novel multi-winner contests (MWC) mechanism for strategic diffusion in social networks. The MWC mechanism satisfies several desirable properties, including false-name-proofness, individual rationality, budget constraint, monotonicity, and subgraph constraint. Numerical experiments on four real-world social network datasets demonstrate that stakeholders can significantly boost participants’ aggregated efforts with proper design of competitions. Our work sheds light on how to design manipulation-resistant mechanisms with appropriate contests.

Socio-Technical Attack Approximation Based on Structural Virality of Information in Social Networks

2021 ◽  
Vol 15 (1) ◽  
pp. 153-172
Author(s):  
Preetish Ranjan ◽  
Abhishek Vaish
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Latent Structure ◽  
The Social ◽  
High Skill ◽  
The Way

A free and easily accessible platform for sharing information over social media has its negatives. It is being misused to intimidate others by exploiting the trust factor inherent within it. This paper is on the persistent pursuit of offering an exquisite solution to address this possible misuse of social media also called STAs and their subsequent impacts on society. These attacks are very sensitive to society and often organized groups with a high skill set are involved to disguise the security agencies. In this work, a model has been proposed to approximate socio-technical attack subject to the structural virality of information in the social network. The work is unique in the sense that previous works are mostly based on statistical values of the network but the proposed work considers the latent structure of the network which is not being reflected from their statistical values. This also paves the way for future researchers to implant other hidden features of nodes and messages circulating within the network which could be helpful for the detection and mitigation of STAs.

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

scholarly journals I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13971-13972
Author(s):  
Yang Qi ◽  
Farseev Aleksandr ◽  
Filchenkov Andrey
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Model Performance ◽  
User Profiling ◽  
Personalized Recommendation ◽  
Modal Data ◽  
Social Media Networks ◽  
The Impact

Nowadays, social networks play a crucial role in human everyday life and no longer purely associated with spare time spending. In fact, instant communication with friends and colleagues has become an essential component of our daily interaction giving a raise of multiple new social network types emergence. By participating in such networks, individuals generate a multitude of data points that describe their activities from different perspectives and, for example, can be further used for applications such as personalized recommendation or user profiling. However, the impact of the different social media networks on machine learning model performance has not been studied comprehensively yet. Particularly, the literature on modeling multi-modal data from multiple social networks is relatively sparse, which had inspired us to take a deeper dive into the topic in this preliminary study. Specifically, in this work, we will study the performance of different machine learning models when being learned on multi-modal data from different social networks. Our initial experimental results reveal that social network choice impacts the performance and the proper selection of data source is crucial.

scholarly journals Study of Automotive Brands Popularity in Indonesia Using Twitter Data

2016 ◽  
Vol 3 (1) ◽  
pp. 23-33
Author(s):  
Stevent Efendi ◽  
Alva Erwin ◽  
Kho I Eng
Keyword(s):  
Social Media ◽  
Social Network ◽  
Sentiment Analysis ◽  
Automotive Industry ◽  
Real World ◽  
The Internet ◽  
Brand Preference ◽  
Twitter Data ◽  
Wide Range ◽  
Widespread Phenomenon

Social media has been a widespread phenomenon in the recent years. People shared a lot of thought in social media, and these data posted on the internet could be used for study and researches. As one of the fastest growing social network, Twitter is a particularly popular social media to be studied because it allows researchers to access their data. This research will look the correlation between Twitter chatter of a brand and the sales of brands in Indonesia. Factors such as sentiment and tweet rate are expected to be able to predict the popularity of a brand. Being one of the biggest industries in Indonesia, automotive industry is an interesting subject to study. A wide range of people buys vehicles, and even gather as communities based on their car or motorcycle brand preference. The Twitter results of sentiment analysis and tweet rate will be compared with real world sales results published by GAIKINDO and AISI.

scholarly journals Who comes to mind? Dynamic construction of social networks

2020 ◽  
Author(s):  
Joseph Bayer ◽  
Neil Anthony Lewis ◽  
Jonathan Stahl
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Real World ◽  
Dynamic Process ◽  
Social Groups ◽  
Social Resources ◽  
Personal Relationships ◽  
Cognitive Mechanisms ◽  
Relational Structures ◽  
Network Technologies

Much remains unknown about moment-to-moment social-network cognition — that is, who comes to mind as we go about our day-to-day lives. Responding to this void, we describe the real-time construction of cognitive social networks. First, we outline the types of relational structures that comprise momentary networks, distinguishing the roles of personal relationships, social groups, and mental sets. Second, we discuss the cognitive mechanisms that determine which individuals are activated — and which are neglected — through a dynamic process. Looking forward, we contend that these overlooked mechanisms need to be considered in light of emerging network technologies. Finally, we chart the next steps for understanding social-network cognition across real-world contexts, along with the built-in implications for social resources and intergroup disparities.

scholarly journals RE-ENGINEERING OF SMART CITY'S BUSINESS PROCESSES BASED ON SOCIAL NETWORKS AND INTERNET OF THINGS

2018 ◽  
Vol 16 (3) ◽  
pp. 275
Author(s):  
Emir Ugljanin ◽  
Dragan Stojanović ◽  
Ejub Kajan ◽  
Zakaria Maamar
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Internet Of Things ◽  
Smart City ◽  
Business Processes ◽  
Smart Cities ◽  
Successful Management ◽  
Complete Integration ◽  
Social Actions

This paper reports our experience with developing a Business-2-Social (B2S) platform that provides necessary support to all this platform’s constituents, namely business processes, social media (e.g., social network), and Internet of Things (IoT). This platform is exemplified with smart cities whose successful management requires a complete integration of IoT and social media capabilities into the business processes implementing user services. To ensure a successful integration, social actions, that a smart city would allow citizens execute, are analyzed in terms of impact of these smart city’s business processes. Reactions to these actions are tracked and then analyzed to improve user services.

scholarly journals tugas review artikel

2019 ◽  
Author(s):  
Arlika Anindya Putri
Keyword(s):  
Social Capital ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Firm Performance ◽  
Positive Impact ◽  
Social Capital Theory ◽  
Capital Theory ◽  
Mediating Role ◽  
The Social

Purpose – The purpose of this study is to develop a structural equation model to explain the complexrelationship between social network and firm performance by introducing the mediating role of trust, sellingcapability and pricing capability.Design/methodology/approach – The research model with hypothesis development was derived basedon the literature. To provide empirical evidence, this study carried out a survey in which the data wereequated with a list of questionnaires with a random survey of 380 small and medium enterprises (SMEs) inthe Indonesian context.Findings – This study indicates that the use of social media in management process will not affect theincreasing firm performance, unless the firms build trust upon social networks. The social network with trustallows the firms to gain a pricing capability and a selling capability, which brings a positive impact on firmperformance. The results also show that the selling and the pricing capabilities become essential following theutilizing the social media, which concerns on trust building.Research limitations/implications – This study focused on the small-to-medium context, which hasconventionally provided an exemplary site for the development of social capital theory but raises issues ofgeneralizability across different contexts.Practical implications – To the managers, it is advisable to encourage their employees to consciouslyexploit the selling capability by enhancing the business networks via social media to achieve the firmperformance.Originality/value – This paper contributes to the social capital theory by explaining the mediating role oftrust in the complex relationship between social network and firm performance. This study provides evidencethat trust plays a pivotal role in social networks, which enable the observed firms to achieve the performance.

The Value of Price Discrimination in Large Social Networks

2021 ◽  
Author(s):  
Jiali Huang ◽  
Ankur Mani ◽  
Zizhuo Wang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Price Discrimination ◽  
Consumer Satisfaction ◽  
Numerical Experiments ◽  
Network Externalities ◽  
Random Networks ◽  
Positive Externalities ◽  
The Social ◽  
Recent Trends

We study the value of price discrimination in large social networks. Recent trends in industry suggest that, increasingly, firms are using information about social network to offer personalized prices to individuals based upon their positions in the social network. In the presence of positive network externalities, firms aim to increase their profits by offering discounts to influential individuals that can stimulate consumption by other individuals at a higher price. However, the lack of transparency in discriminative pricing may reduce consumer satisfaction and create mistrust. Recent research focuses on the computation of optimal prices in deterministic networks under positive externalities. We want to answer the question of how valuable such discriminative pricing is. We find, surprisingly, that the value of such pricing policies (increase in profits resulting from price discrimination) in very large random networks are often not significant. Particularly, for Erdös–Renyi random networks, we provide the exact rates at which this value decays in the size of the networks for different ranges of network densities. Our results show that there is a nonnegligible value of price discrimination for a small class of moderate-sized Erdös–Renyi random networks. We also present a framework to obtain bounds on the value of price discrimination for random networks with general degree distributions and apply the framework to obtain bounds on the value of price discrimination in power-law networks. Our numerical experiments demonstrate our results and suggest that our results are robust to changes in the model of network externalities. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

Analyzing Social Networks to Mine Important Friends

2013 ◽  
pp. 90-104 ◽  
Author(s):  
Carson K.-S. Leung ◽  
Irish J. M. Medina ◽  
Syed K. Tanbeer
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Social Networking Sites ◽  
Web Based ◽  
The Social ◽  
Social Entity ◽  
Social Entities ◽  
Media Data ◽  
Media Mining

The emergence of Web-based communities and social networking sites has led to a vast volume of social media data, embedded in which are rich sets of meaningful knowledge about the social networks. Social media mining and social network analysis help to find a systematic method or process for examining social networks and for identifying, extracting, representing, and exploiting meaningful knowledge—such as interdependency relationships among social entities in the networks—from the social media. This chapter presents a system for analyzing the social networks to mine important groups of friends in the networks. Such a system uses a tree-based mining approach to discover important friend groups of each social entity and to discover friend groups that are important to social entities in the entire social network.

Role of Social Media in Tourism

2015 ◽  
pp. 142-162
Author(s):  
Vipin K. Nadda ◽  
Sumesh Singh Dadwal ◽  
Dirisa Mulindwa ◽  
Rubina Vieira
Keyword(s):  
Social Networks ◽  
Information Technology ◽  
Social Media ◽  
Social Network ◽  
Social Networking ◽  
Web Sites ◽  
User Generated Content ◽  
Major Shift ◽  
Tourism And Hospitality

Revolutionary development in field of communication and information technology have globally opened new avenue of marketing tourism and hospitality products. Major shift in web usage happened when Napster in 1999 released peer-to-peer share media and then with pioneer social networking websites named ‘Six Degrees'. This kind of interactive social web was named as ‘Web 2.0'. It would create openness, community and interaction. Web2. is also known as Social media base. Social media is incudes “all the different kinds of content that form social networks: posts on blogs or forums, photos, audio, videos, links, profiles on social networking web sites, status updates and more”. It allows people to create; upload post and share content easily and share globally. Social media allows the creation and exchange of user-generated content and experiences online. Thus, social media is any kind of information we share with our social network, using social networking web sites and services.

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