Trust and manipulation in social networks

We investigate the role of manipulation in a model of opinion formation where agents have opinions about some common question of interest. Agents repeatedly communicate with their neighbors in the social network, can exert some effort to manipulate the trust of others, and update their opinions taking weighted averages of neighbors’ opinions. The incentives to manipulate are given by the agents’ preferences. We show that manipulation can modify the trust structure and lead to a connected society, and thus, make the society reaching a consensus. Manipulation fosters opinion leadership, but the manipulated agent may even gain influence on the long-run opinions. In sufficiently homophilic societies, manipulation accelerates (slows down) convergence if it decreases (increases) homophily. Finally, we investigate the tension between information aggregation and spread of misinformation. We find that if the ability of the manipulating agent is weak and the agents underselling (overselling) their information gain (lose) overall influence, then manipulation reduces misinformation and agents converge jointly to more accurate opinions about some underlying true state

Privacy, Sharing, and Trust: The Facebook Study

Using sharing on Facebook as a case study, this Article presents empirical evidence suggesting that trust is a significant factor in individuals’ willingness to share personal information on online social networks. I then make two arguments, one that explains why Facebook is designed the way it is and one that calls for legal protection against unfair manipulation of users. I argue that Facebook is built on trust: the trust that exists between friends and the trust that exists between users and the platform. In particular, I describe how Facebook designs its platform and interface to leverage the trust we have in our friends to nudge us to share. Sometimes, that helps create a dynamic social environment: knowing what our friends are doing helps us determine when it is safe to interact. Other times, Facebook leverages trust to manipulate us into sharing information with advertisers. This should give us pause. Because Facebook uses trust-based design, users may be confused about the privacy effects of their behavior. Federal and state consumer and privacy protection regulators should step in

Where The Two Trusts Meet: How Social Trust Influences Political Trust In The New Media Environment

In the modern democratic society, where it is difficult to get to know politicians in person or to fully internalize the complex political system, news articles strongly influence the forming and updating of political trust. Technical developments have created the layer of one’s personal network between traditional media and its audience by allowing one to share any article with a few clicks. Reflecting this change in how one shares information, this dissertation investigates how online social trust influences one’s political trust, a more deep-seated attitude. There is little agreement on how to conceptualize and measure political trust. Study 1 shows how the NPTMS (New Political Trust Measurement Survey) demonstrates a gap between how the public creates the meaning of political trust and how scholars do. It then proposes more reliable and valid measures of political trust. To better simulate information exchange online, this dissertation introduces the concept of OIST (online interpersonal social trust), trust in a particular person from one’s online social networks. Study 2 looks at the factors that lead to OIST and explores how to manipulate it in an experimental setting. By combining two different manipulation strategies—partner profile and flashcard exercise—OIST was successfully manipulated without influencing other types of social trust. Based on the NPTMS and OIST manipulation strategies, Study 3 connects OIST with political trust and experimentally demonstrates that they are causally related but moderated by the valence of the shared; receiving an article negatively depicting the government from a person one trusts resulted in a lower level of trust in the subjects of the article. This dissertation uses OIST to also reflect the recent changes in how the public consumes news. It offers evidence that “regular people,” who are not necessarily experts or opinion leaders in a particular subject, can make others significantly readjust their levels of political trust. As an increasing number of people consume news through their online social networks, we should note that each individual can influence another’s trust in government, and that the effect may accumulate with continued interactions

Where is the trust? For the good of the people

In an era where the public has greater access to information than ever before, why is it that social capital in many communities is so divided and diminished? Traditionally people have experienced and generated social capital through direct contact with families and social spaces, including neighbourhoods, communities, clubs and the workplace. Nowadays, many relationships and networks operate at a global level and in cyber-space – enabled through technology and screen-mediated interactions. While there are many benefits to contemporary technologies and innovations, including new forms of sociability, these same developments have also resulted in a loss of sociability; a loss of social capital, social cohesion and trust in institutions. Western democratic societies, including Australia, appear to have become open to the exploitation of change and uncertainty in communities, amplified by propagandists and the manipulation of both mainstream and social media; to sow social discord and create fear and uncertainty, including a loss of trust in scientific research originating from universities. It is the trust in knowledge and research that has guided many governments to look beyond political cycles and plan for inclusive, tolerant societies, receptive to population diversity creating unique social assets. It is in this context that the development of new forms of social spaces, including well-designed public buildings, prospectively hold the regeneration of social capital in pursuit of more economically successful and socially cohesive communities. Regional Australia, including the regional city of Townsville, is negotiating this shift

Social media and social innovation

All parts of human communication existence has been improved through the use of new media technologies and especially through the use of social media which is reflected directly and indirectly on social innovations sui generis. Social innovation should be the game of ideas of equal interaction of different subject using the special life within the life that exists in the virtual world of new technologies. To able to use social media in proper way within social innovation process we have to take into the account that social media are: cheapest form of interaction; accessibility – everybody can be involved within social innovation through social media networks – previously it was reserved only for the organizations well equipped with equipment and personnel. Social media can be used for producing opportunities for creative construction of a new model of citizen participation through education within social innovation process while, in the same time, journalists becomes a mediators of democratic participations of citizens. Social networks have emerged as a critical factor in information dissemination, search, marketing and influence discovery. The capacity of any society to create of steady flow of social innovations depends on a huge amount of presumptions even to be able to link and interact, in proper way, of social media and social innovation, but it is very difficult to control social media, regardless how skilled individuals are involved as a starting point of social innovation dissemination. So, where is the solution? Within the society as the whole, having in mind that manipulation should be replaced with transparency and responsibility of each step of social innovation process through social media. Why? The one word is the answer – it creates TRUST. Creation of transparency and responsibility is both, direct and indirect creation of the most important issues for the proper existence of society – TRUST in the existence system. The most important for connecting people, ideas and resources, within the field of the use of digital technology, are the intermediaries. Namely, those are the social networks which will connect people, ideas and resources for the social innovations, through social media and interacting with them. Of course, within Social media and Social innovations the most important intermediaries are the people, depending on their wishes and capabilities to do the change and to be a change – for the benefit of the society as the whole

Using Noninvasive Brain Measurement to Explore the Psychological Effects of Computer Malfunctions on Users during Human-Computer Interactions

In today’s technologically driven world, there is a need to better understand the ways that common computer malfunctions affect computer users. These malfunctions may have measurable influences on computer user’s cognitive, emotional, and behavioral responses. An experiment was conducted where participants conducted a series of web search tasks while wearing functional nearinfrared spectroscopy (fNIRS) and galvanic skin response sensors. Two computer malfunctions were introduced during the sessions which had the potential to influence correlates of user trust and suspicion. Surveys were given after each session to measure user’s perceived emotional state, cognitive load, and perceived trust. Results suggest that fNIRS can be used to measure the different cognitive and emotional responses associated with computer malfunctions. These cognitive and emotional changes were correlated with users’ self-report levels of suspicion and trust, and they in turn suggest future work that further explores the capability of fNIRS for the measurement of user experience during human-computer interactions

An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A novel framework to prevent manipulation behaviour in consensus reaching process under social network group decision making is proposed, which is based on a theoretically sound optimal feedback model. The manipulation behaviour classification is twofold: (1) ‘individual manipulation’ where each expert manipulates his/her own behaviour to achieve higher importance degree (weight); and (2) ‘group manipulation’ where a group of experts force inconsistent experts to adopt specific recommendation advices obtained via the use of fixed feedback parameter. To counteract ‘individual manipulation’, a behavioural weights assignment method modelling sequential attitude ranging from ‘dictatorship’ to ‘democracy’ is developed, and then a reasonable policy for group minimum adjustment cost is established to assign appropriate weights to experts. To prevent ‘group manipulation’, an optimal feedback model with objective function the individual adjustments cost and constraints related to the threshold of group consensus is investigated. This approach allows the inconsistent experts to balance group consensus and adjustment cost, which enhances their willingness to adopt the recommendation advices and consequently the group reaching consensus on the decision making problem at hand. A numerical example is presented to illustrate and verify the proposed optimal feedback model

Understanding Potential Cyber-Armies in Elections: A Study of Taiwan

Currently, online social networks are essential platforms for political organizations to monitor public opinion, disseminate information, argue with the opposition, and even achieve spin control. However, once such purposeful/aggressive articles flood social sites, it would be more difficult for users to distinguish which messages to read or to trust. In this paper, we aim to address this issue by identifying potential “cyber-armies/professional users” during election campaigns on social platforms. We focus on human-operated accounts who try to influence public discussions, for instance, by publishing hundreds/thousands of comments to show their support or rejection of particular candidates. To achieve our objectives, we collected activity data over six months from a prominent Taiwan-based social forum before the 2018 national election and applied a series of statistical analyses to screen out potential targets. From the results, we successfully identified several accounts according to distinctive characteristics that corresponded to professional users. According to the findings, users and platforms could realize potential information manipulation and increase the transparency of the online society

Controllability of Social Networks and the Strategic Use of Random Information

This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception. Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network, and considers two well-known strategies for influencing social contexts. One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad-hoc metrics defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests. The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills, supporting our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable