scholarly journals Re-Fake: Klasifikasi Akun Palsu di Sosial Media Online menggunakan Algoritma RNN

2021 ◽  
Vol 3 ◽  
pp. 191-200
Author(s):  
Putra Wanda ◽  
Marselina Endah Hiswati ◽  
Mohammad Diqi ◽  
Romana Herlinda
Keyword(s):  
Social Media ◽  
Social Network ◽  
Online Social Network

Online Social Network (OSN) adalah aplikasi social media yang memungkinkan komunikasi publik dan berbagi informasi. Namun, akun palsu di OSN dapat menyebarkan informasi palsu dengan sumber yang tidak diketahui. Ini adalah tugas yang menantang untuk mendeteksi akun berbahaya dalam sistem OSN yang besar. Keberadaan akun palsu atau akun yang tidak dikenal di OSN dapat menjadi masalah serius dalam menjaga privasi data. Berbagai komunitas telah mengusulkan banyak teknik untuk menangani akun palsu di OSN, termasuk teknik hitam-putih berbasis aturan hingga pendekatan pembelajaran. Oleh karena itu, dalam penelitian ini kami mengusulkan model klasifikasi menggunakan RNN untuk mendeteksi akun palsu secara akurat dan efektif. Kami melakukan penelitian ini dalam beberapa langkah, termasuk mengumpulkan dataset, pra-pemrosesan, ekstraksi, melatih model kami menggunakan RNN. Berdasarkan hasil eksperimen, model yang kami usulkan dapat menghasilkan akurasi yang lebih tinggi daripada model pembelajaran konvensional.

scholarly journals Social Media Use and Innovations: Introduction to the Special Issue

2016 ◽  
Vol 3 (1) ◽  
pp. 1-3 ◽  
Author(s):  
Petter Bae Brandtzaeg ◽  
Asbjørn Følstad
Keyword(s):  
Social Media ◽  
Social Network ◽  
Civic Engagement ◽  
Media Use ◽  
Online Social Network ◽  
Special Issue ◽  
Social Media Use

This special issue on "Social media use and innovations" of the Journal of Media Innovation provides an engaging view into innovative uses of social media as well as approaches for utilizing social media in innovation.  With three papers included, we cover experiences with an online social network for children (Stephanie Valentine and Tracy Hammond), design by youth for youth in projects on social media for civic engagement (Henry Mainsah, Petter Bae Brandtzaeg, and Asbjørn Følstad), and social platforms for corporate and community innovation (Marika Lüders).

scholarly journals Social Media and Protest Participation: Evidence From Russia

Econometrica ◽  
2020 ◽  
Vol 88 (4) ◽  
pp. 1479-1514 ◽  
Author(s):  
Ruben Enikolopov ◽  
Alexey Makarin ◽  
Maria Petrova
Keyword(s):  
Social Media ◽  
Social Network ◽  
Online Social Network ◽  
Communication Technologies ◽  
Threshold Behavior ◽  
Collective Action Problem ◽  
Governmental Support ◽  
The Government ◽  
The City ◽  
Protest Activity

Do new communication technologies, such as social media, alleviate the collective action problem? This paper provides evidence that penetration of VK, the dominant Russian online social network, led to more protest activity during a wave of protests in Russia in 2011. As a source of exogenous variation in network penetration, we use the information on the city of origin of the students who studied with the founder of VK, controlling for the city of origin of the students who studied at the same university several years earlier or later. We find that a 10% increase in VK penetration increased the probability of a protest by 4.6% and the number of protesters by 19%. Additional results suggest that social media induced protest activity by reducing the costs of coordination rather than by spreading information critical of the government. We observe that VK penetration increased pro‐governmental support, with no evidence of increased polarization. We also find that cities with higher fractionalization of network users between VK and Facebook experienced fewer protests, and the effect of VK on protests exhibits threshold behavior.

scholarly journals Online social network relationships influenced on a retweeting

2020 ◽  
Vol 20 (2) ◽  
pp. 1037
Author(s):  
Iman K. Abbood ◽  
Saad Talib Hasson
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Correlation Coefficient ◽  
Social Relationship ◽  
Online Social Network ◽  
Ease Of Use ◽  
Breaking News ◽  
Main Effect ◽  
Promising Source

<p>Social network users spending a lot of time to post, search, interact and read the news on blogging platforms. In this era, social media is becoming a suitable place for discovering and exchanging new updates. However, Common social media helps the user to share his news online by a one-click. The ease-of-use leads to present novel breaking news to show up first on micro blogs. Twitter is one of the well-known micro blogging platforms with more than 250 million users, in which retweeting is a manageable way to share and sawing news. It is significant to foretell the retweeting and influence in a social relationship. The Correlation Coefficient formula has been used to determine the level of correlation between a user and his retweeters (followers, friends, and strangers) in social networks. Such correlation can be reached by utilizing the collected user information on Twitter with some features which have a main effect on retweet behavior. In this study, the focus is on particular friends, followers, and a retweet to be the promising source of relationships between users of social media. Experimental results based on twitter dataset showed that the Correlation Coefficient formula can be used as a predicting model, and it is a general framework to gain better fulfillment in calculating the correlation between the user, friends, and followers in social networks..  Their influence on the accuracy in predicting a retweet is also accomplished.</p>

scholarly journals Polarization in social media assists influencers to become more influential: analysis and two inoculation strategies

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ivan Garibay ◽  
Alexander V. Mantzaris ◽  
Amirarsalan Rajabi ◽  
Cameron E. Taylor
Keyword(s):  
Social Media ◽  
Social Network ◽  
Uniform Distribution ◽  
Real World ◽  
Online Social Network ◽  
World Systems ◽  
Methodological Framework ◽  
Key Factors ◽  
User Privacy ◽  
Theoretical Premise

AbstractThis work explores simulations of polarized discussions from a general and theoretical premise. Specifically the question of whether a plausible avenue exists for a subgroup in an online social network to find a disagreement beneficial and what that benefit could be. A methodological framework is proposed which represents key factors that drives social media engagement including the iterative accumulation of influence and the dynamics for the asymmetric treatment of messages during a disagreement. It is shown that prior to a polarization event a trend towards a more uniform distribution of relative influence is achieved which is then reversed by the polarization event. The reasons for this reversal are discussed and how it has a plausible analogue in real world systems. A pair of inoculation strategies are proposed which aim at returning the trend towards uniform influence across users while refraining from violating user privacy (by remaining topic agnostic) and from user removal operations.

Working Adults' Buying Intention Through Online Social Network

2021 ◽  
Vol 17 (4) ◽  
pp. 92-116
Author(s):  
Syed Shah Alam ◽  
Chieh-Yu Lin ◽  
Mohd Helmi Ali ◽  
Nor Asiah Omar ◽  
Mohammad Masukujjaman
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Perceived Risk ◽  
Word Of Mouth ◽  
Online Social Network ◽  
Perceived Value ◽  
Online Social Media ◽  
Starting Point

Most businesses have online social media presence; therefore, understanding of working adult's perception on buying through online social networks is vital. The aim of this study is to examine the effect of perceived value, sociability, usability, perceived risk, trust, and e-word-of-mouth on buying intention through online social network sites. The research model for this study was developed based on the literature on information system research. This study adopted convenient sampling of non-probability sampling procedure. Data were collected through self-administered questionnaire, and PLS-based path analysis was used to analyse responses. The findings of the study shows that perceived value, sociability, usability, e-word-of-mouth, attitude, and subjective norm are significant constructs of buying intention through online social networks. This research can serve as a starting point for online shopping research through online social media while encouraging further exploration and integration addition adoption constructs.

scholarly journals Impact of Entertainment Motivational Drivers on User Acceptance of Online Social Network Banner Advertising: A Gratification Perspective

2017 ◽  
Vol 20 (1) ◽  
pp. 19-47 ◽  
Author(s):  
Imran Anwar Mir
Keyword(s):  
Social Media ◽  
Social Network ◽  
University Students ◽  
Business Model ◽  
Online Social Network ◽  
Social Network Sites ◽  
Time Factors ◽  
User Acceptance

Abstract Social media has phenomenally changed the communication landscape. Particularly social network sites have received enormous popularity and user acceptance globally. The business model of many social network sites is based on advertising. The survival of these social network sites depends on the user acceptance of advertising appearing on these websites. Users usually accept the advertising which is consistent with their motivations for using social network sites. The current study examines the underlying dimensions of entertainment motivation for using social network sites and their impact on user acceptance of social network advertising. Analysis of data from 450 university students show entertainment motivation for using social network sites a multidimensional (SNSs) construct consisting of enjoyment, social escapism, relaxation and pass time factors. Furthermore, the results exhibit that SNSs entertainment motivation partially impacts user acceptance of social network advertising.

scholarly journals The Role of Social Media in Disaster Recovery Following Hurricane Harvey

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Courtney Page-Tan
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Disaster Response ◽  
Disaster Recovery ◽  
Online Social Network ◽  
Stress Test ◽  
High Water ◽  
Houston Area

AbstractHurricane Harvey was social media's first real stress test as a disaster response and recovery mechanism. A confluence of conditions makes it an ideal case study of social media's role in disaster recovery: the lack of a government-issued evacuation order, a call from government leadership for willing and able volunteers with a boat or high-water vehicle to perform life-saving rescues, and wide-spread adoption of social media platforms in the Houston area. While research on online social networks and disasters continues to grow, social scientists know little about how these online networks transform during a crisis and, further, how they drive disaster outcomes. With two original datasets, this study investigates how Houston's online social network transformed during Hurricane Harvey (2017), and the relationship between social media activity and post-Harvey recovery. The findings of a social network analysis (N= 2,387,610) and subsequent statistical analyses reveal the Houston-area online social network grew denser, clustered, and more efficient during the disaster. A spatial analysis and three separate regression models of activity before, during, and after Hurricane Harvey reveal that among 333 Nextdoor Neighborhoods, hyperlocal social media activity was a statistically significant predictor of the rate of rebuilding in these geographically based online communities. These findings suggest that policy and decision-makers should invest into online and offline hyperlocal social networks well before a disaster strikes, and leverage resources and legislation to maintain and strengthen the telecommunications and energy infrastructure that supports access to social media and telecommunications infrastructure during a time of crisis.

scholarly journals Detecting Spam Bots on Social Network

2021 ◽  
Vol 11 (2) ◽  
pp. 850-860
Author(s):  
A. Gnanasekar
Keyword(s):  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Online Social Network ◽  
Detection Accuracy ◽  
Social Media Site ◽  
User Activity ◽  
A New Technique ◽  
User Knowledge ◽  
Being Moved

Bots have made an appearance on social media in a variety of ways. Twitter, for instance, has been particularly hard hit, with bots accounting for a shockingly large number of its users. These bots are used for nefarious purposes such as disseminating false information about politicians and inflating celebrity expectations. Furthermore, these bots have the potential to skew the results of conventional social media research. With the multiple increases in the size, speed, and style of user knowledge in online social networks, new methods of grouping and evaluating such massive knowledge are being explored. Getting rid of malicious social bots from a social media site is crucial. The most widely used methods for identifying fraudulent social bots focus on the quantitative measures of their actions. Social bots simply mimic these choices, leading to a low level of study accuracy. Transformation clickstream sequences and semi-supervised clustering were used to develop a new technique for detecting malicious social bots. This method considers not only the probability of user activity clickstreams being moved, but also the behavior's time characteristic. The detection accuracy for various kinds of malware social bots by the detection technique assisted transfer probability of user activity clickstreams will increase by a mean of 12.8 percent, as per results from our research on real online social network sites, compared to the detection method funded estimate of user behaviour.

THE MECHANISM OF LINKAGES BETWEEN ONLINE COMMUNITY PARTICIPATION AND FESTIVAL ATTENDANCE – A CASE STUDY OF A CHINESE MUSIC FESTIVAL

2020 ◽  
Author(s):  
Weng Si (Clara) Lei ◽  
Chun Chen (Claudia) Li
Keyword(s):  
Social Media ◽  
Social Network ◽  
Online Community ◽  
Online Social Network ◽  
Structured Interviews ◽  
New Members ◽  
Music Festival ◽  
Chinese Music ◽  
Online Music ◽  
Participation Motives

Online social network participation, and its impacts on festival attendees’ motivation, have been investigated in previous studies. However, the results have been inconclusive. Social network participation motives have also been researched but have mostly been limited to Facebook and other social media from the West. Social media participation motives in the East, for example in China, and its causes and effects on music festival attendance have remained underexplored. This study adopted a qualitative approach, using semi-structured interviews and netnography to empirically examine the connection between online social network participation and music festival attendance. Data collection included using netnography to explore a music festival social network chat group (online community) and then conducting in-depth interviews with festival attendees who were active members of the online community. The study sheds new light on festival attendees’ motives for online social network participation, a plausible mechanism and model to explain how an online music festival community sustains and connects its old and new members.

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