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

Ming-Hung Wang; Nhut-Lam Nguyen; Shih-chan Dai; Po-Wen Chi; Chyi-Ren Dow

doi:10.3390/su12062248

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

Sustainability ◽

10.3390/su12062248 ◽

2020 ◽

Vol 12 (6) ◽

pp. 2248

Author(s):

Ming-Hung Wang ◽

Nhut-Lam Nguyen ◽

Shih-chan Dai ◽

Po-Wen Chi ◽

Chyi-Ren Dow

Keyword(s):

Social Networks ◽

Public Opinion ◽

Online Social Networks ◽

National Election ◽

Statistical Analyses ◽

Election Campaigns ◽

Political Organizations ◽

Activity Data ◽

Information Manipulation

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.

Download Full-text

Fake News im Wahlkampf

10.5771/9783748926832 ◽

2021 ◽

Author(s):

Jessica Flint

Keyword(s):

Social Networks ◽

Public Opinion ◽

Fundamental Rights ◽

Election Campaigns ◽

Fake News ◽

Forming Process ◽

Private Companies ◽

The Future

The urgency of regulating fake news on social networks regarding election campaigns is more evident than ever. This poses considerable difficulties for legislative practice. It is important to consider the fundamental rights of the parties involved without the state's influence on the formation of public opinion becoming too great. The current options of reacting to fake news do not suffice to ensure a free opinion-forming process. This publication makes an innovative proposal as to how social networks – especially Facebook – can be regulated in the future in such a way that the discourse is strengthened and the alarming influence of private companies on the formation of opinion is limited.

Download Full-text

Cross-network propagation model of public opinion information and its control in coupled double-layer online social networks

Aslib Journal of Information Management ◽

10.1108/ajim-04-2021-0126 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Yun Li ◽

Jiakun Wang

Keyword(s):

Social Networks ◽

Public Opinion ◽

Double Layer ◽

Online Social Networks ◽

Early Stage ◽

Intervention Strategy ◽

Propagation Model ◽

Content Type ◽

Propagation Law ◽

Network Propagation

PurposeIn modern society, considering the multi-channel of public opinion information (public opinion) propagation and its strong influence on social development, it is necessary to study its propagation law and discuss the intervention strategy in online social networks (OSN).Design/methodology/approachFirst, a conceptual model of double-layer OSN was constructed according to their structural characteristics. Then, a cross-network propagation model of public opinion in double-layer OSN was proposed and discussed its spreading characteristics through numerical simulations. Finally, the control strategy of public opinion, especially the timing and intensity of intervention were discussed.FindingsThe results show that the double-layer OSN promotes the propagation of public opinion, and the propagation of public opinion in double-layer OSN has the characteristics of that in two single-layer OSN. Compared with the intervention intensity, the regulator should give the priority to the timing of intervention and try to intervene in the early stage of public opinion propagation.Practical implicationsThis study may help the regulators to respond to the propagation of public opinion in OSN more actively and reasonably.Originality/valueThis research has a deep comprehension of the cross-network propagation rules of public opinion and manages the propagation of public opinion.

Download Full-text

Internet Public Opinion Monitoring Model Based on Cloud Computing

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.404.744 ◽

2013 ◽

Vol 404 ◽

pp. 744-747

Author(s):

Zhong Tang He ◽

Xiao Qing Zhang ◽

Feng Wei Zhao ◽

Tong Kai Ji

Keyword(s):

Social Networks ◽

Cloud Computing ◽

Public Opinion ◽

Social Network ◽

Online Social Networks ◽

Rapid Development ◽

The Public ◽

Mass Data ◽

Model Based ◽

Monitoring Model

With the rapid development of online social networks, such as social network services, BBS, micro-blog and online community, et al., a two-way communication and new media age has been gradually coming. Each one can create their own content and publish the news quickly through online social networks on Internet. Thus, mass data has brought severe challenge to public opinion monitoring. As a kind of novel information computing model, cloud computing technology can effectively deal with the calculation and storage of mass data. In this paper, the public opinion monitoring model based on cloud computing environment is introduced, which can mine and analyze large scale collected data, realize detection and tracking of hot topics, perform social network analysis on the BBS and visualize the analysis results. The public opinion monitoring system based on cloud can provide timely sensitive information and deal with public crisis efficiently. Finally, the advantage is analyzed when cloud computing is applied to public opinion monitoring.

Download Full-text

Cross-site Prediction on Social Influence for Cold-start Users in Online Social Networks

ACM Transactions on the Web ◽

10.1145/3409108 ◽

2021 ◽

Vol 15 (2) ◽

pp. 1-23

Author(s):

Qingyuan Gong ◽

Yang Chen ◽

Xinlei He ◽

Yu Xiao ◽

Pan Hui ◽

...

Keyword(s):

Social Networks ◽

Social Influence ◽

Online Social Networks ◽

Cold Start ◽

Learning Technologies ◽

Viral Marketing ◽

Supervised Machine Learning ◽

Activity Data ◽

Public Data ◽

Influential Users

Online social networks (OSNs) have become a commodity in our daily life. As an important concept in sociology and viral marketing, the study of social influence has received a lot of attentions in academia. Most of the existing proposals work well on dominant OSNs, such as Twitter, since these sites are mature and many users have generated a large amount of data for the calculation of social influence. Unfortunately, cold-start users on emerging OSNs generate much less activity data, which makes it challenging to identify potential influential users among them. In this work, we propose a practical solution to predict whether a cold-start user will become an influential user on an emerging OSN, by opportunistically leveraging the user’s information on dominant OSNs. A supervised machine learning-based approach is adopted, transferring the knowledge of both the descriptive information and dynamic activities on dominant OSNs. Descriptive features are extracted from the public data on a user’s homepage. In particular, to extract useful information from the fine-grained dynamic activities that cannot be represented by the statistical indices, we use deep learning technologies to deal with the sequential activity data. Using the real data of millions of users collected from Twitter (a dominant OSN) and Medium (an emerging OSN), we evaluate the performance of our proposed framework to predict prospective influential users. Our system achieves a high prediction performance based on different social influence definitions.

Download Full-text

Evolutionary Game Model of Public Opinion Information Propagation in Online Social Networks

IEEE Access ◽

10.1109/access.2020.3006150 ◽

2020 ◽

Vol 8 ◽

pp. 127732-127747 ◽

Cited By ~ 2

Author(s):

Jiakun Wang ◽

Xinhua Wang ◽

Li Fu

Keyword(s):

Social Networks ◽

Public Opinion ◽

Online Social Networks ◽

Evolutionary Game ◽

Game Model ◽

Information Propagation

Download Full-text

Detection of Induced Activity in Social Networks: Model and Methodology

Future Internet ◽

10.3390/fi13110297 ◽

2021 ◽

Vol 13 (11) ◽

pp. 297

Author(s):

Dmitrii Gavra ◽

Ksenia Namyatova ◽

Lidia Vitkova

Keyword(s):

Social Networks ◽

Social Media ◽

Public Opinion ◽

Civil Society ◽

Theoretical Background ◽

Election Campaigns ◽

Special Operations ◽

The Public ◽

Political Project ◽

Political Election

This paper examines the problem of social media special operations and especially induced support in social media during political election campaigns. The theoretical background of the paper is based on the study fake activity in social networks during pre-election processes and the existing models and methods of detection of such activity. The article proposes a methodology for identifying and diagnosing induced support for a political project. The methodology includes a model of induced activity, an algorithm for segmenting the audience of a political project, and a technique for detecting and diagnosing induced support. The proposed methodology provides identification of network combatants, participants of social media special operations, influencing public opinion in the interests of a political project. The methodology can be used to raise awareness of the electorate, the public, and civil society in general about the presence of artificial activity on the page of a political project.

Download Full-text