scholarly journals Detection of Malicious Data in Twitter Using Machine Learning Approaches

2021 ◽  
Vol 12 (3) ◽  
pp. 4951-4958
Author(s):  
B.Mukunthan Et. al.
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Digital Media ◽  
Online Social Networks ◽  
Media Culture ◽  
Learning Approaches ◽  
Traditional Media ◽  
Misleading Information ◽  
Online Social Media ◽  
False News

: Unlike traditional media social media is populated by unknown individuals who can broadcast whatever they like. This online social media culture is dynamic in its nature and transition to digital media is becoming a trend among people. In upcoming years the use of traditional media will decline, and the increasing use of Online Social Networks(OSNs) blur the actual information of the traditional media. The information generated by the authentic users gives useful information to the general users, on the other hand,Spammers spread irrelevant or misleading information that makes social media a plot for false news. So unwanted text or vulnerable links can be distributed to specific users. These false texts are anonymous and sometimes linked with potential URLs. Due to data restrictions and communication categories, the current systems do not deserve an exact statistical classification for a piece of news. We will study different research papers using various techniques for master training in the prediction and detection of malicious data on social networks online. We tried to find spam tweets from the tweets collected by using Enhanced Random forest classifications and NaiveBayes in this research. To evaluate the work, different validation metrics such as F1-scoring, accurcy and precision values are calculated.

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.

Privacy Control of Photo Sharing in Online Social Media

2020 ◽  
Vol 17 (9) ◽  
pp. 4692-4697
Author(s):  
Radhika Goriparthi ◽  
Kanyakumari Jagadish Basani
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Data Sharing ◽  
Online Social Networks ◽  
Facial Recognition ◽  
Recognition System ◽  
Online Social Media ◽  
Photo Sharing ◽  
Facial Recognition System ◽  
Prior Permission

Online Social Networks were famous for the data sharing etc., they have many features like chatting, photo sharing etc. A photo can be leaked without prior permission of the owner. A mechanism was developed to allow each individual in the group aware of the photo posting activity. An efficient facial recognition system that can recognize two different photos was designed. Only the owner of the photo can share the photo, this system is superior to other systems in terms of recognition ratio. This application is developed on the windows platform.

scholarly journals SentiFlow: An Information Diffusion Process Discovery Based on Topic and Sentiment from Online Social Networks

2018 ◽  
Vol 10 (8) ◽  
pp. 2731 ◽  
Author(s):  
Berny Carrera ◽  
Jae-Yoon Jung
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Diffusion Process ◽  
Online Social Networks ◽  
Information Diffusion ◽  
Latent Dirichlet Allocation ◽  
Probabilistic Approach ◽  
Digital Era ◽  
Online Social Media ◽  
User Comments

In this digital era, people can become more interconnected as information spreads easily and quickly through online social media. The rapid growth of the social network services (SNS) increases the need for better methodologies for comprehending the semantics among the SNS users. This need motivated the proposal of a novel framework for understanding information diffusion process and the semantics of user comments, called SentiFlow. In this paper, we present a probabilistic approach to discover an information diffusion process based on an extended hidden Markov model (HMM) by analyzing the users and comments from posts on social media. A probabilistic dissemination of information among user communities is reflected after discovering topics and sentiments from the user comments. Specifically, the proposed method makes the groups of users based on their interaction on social networks using Louvain modularity from SNS logs. User comments are then analyzed to find different sentiments toward a subject such as news in social networks. Moreover, the proposed method is based on the latent Dirichlet allocation for topic discovery and the naïve Bayes classifier for sentiment analysis. Finally, an example using Facebook data demonstrates the practical value of SentiFlow in real world applications.

scholarly journals Detecting Misleading Information on COVID-19 : A Machine Learning Perspective

2021 ◽  
Vol 12 (3) ◽  
pp. 4918-4926
Author(s):  
M.Arunkrishna Et. al.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Handheld Devices ◽  
Fake News ◽  
Negative Effects ◽  
Misleading Information ◽  
Commercial Purpose ◽  
Rapid Pace ◽  
False News ◽  
Best Fit

Online Social networks become a popular way for sharing information among people. With increasing technology like Wi-Fi, Wi-Max ,3G/4G along with handheld devices like smartphones and tablets, popular applications such as Instagram, Facebook, Twitter and YouTube, becomes a dominant platform for  news and entertainment. The extensive use of these social networks has an incredible influence on sharing news among people It holds both positive and negative effects of its own. Because of it’s high popularity,Online Social Networks(OSNs),has become the target for spammers. Also, false news for different political and commercial purpose has been evolving in the large count and spread worldwide. After the spread of COVID-19, there had been a lot of confusion and pitfalls on the topic of who to believe and who should be rejected. With the advent of time, several companies like Facebook, and Twitter joined hands to identify the news and regard it authentic or not. This effort was very hard for people, as the news are spreading at a rapid pace, no matter how many people are upon the task, the rate of expansion of news is always faster than the rate of evaluation of whether the news is authentic or not. Additionally, it can be observed that the news cannot be regarded as fake or true before careful evaluation. This evaluation is based on the results. So it is important to create a method for identifying fake news and distinguishing it from individuals. Thus, the paper evaluates several models in order to find the best fit with the highest level of accuracy.

Grey social media engagement analysis

2016 ◽  
Vol 6 (2) ◽  
pp. 233-245 ◽  
Author(s):  
Camelia Delcea
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Online Advertising ◽  
Strong Relationship ◽  
Content Type ◽  
Online Social Media ◽  
Social Media Engagement ◽  
The Right

Purpose – Recent studies have shown that customers are more likely to buy a certain product or service from a company they can follow or contact on social media. Moreover, the customers feel a stronger relationship with the companies they are interacting in the virtual networks. But have the companies succeed in getting everything from this strong relationship? Are their online advertising campaigns getting to the right customers? Is there any connection between the social media engagement and the decisions users are taking? This is going to be shaped in this paper through a grey analysis applied to the selected variables. The paper aims to discuss these issues. Design/methodology/approach – As the nature of the relationships created in the online social networks is characterized by incomplete information, the analysis will make used of the concepts and means offered by the grey systems theory, a theory that have obtained good results over the time when used on uncertain situations. Findings – By applying a grey relational analysis (GRA) to the considered variables, a strong relationship between the decision easiness and both time spent on social media platforms and number of the accessed websites has been identified. Moreover, it has been determined that the decision happiness is closely related to the companies’ websites and their commercials. Research limitations/implications – The present paper shapes the relationship between the usage of online social media and consumers’ decision-making process and decision-making happiness. Due to the fact that the online social media includes billions of users worldwide, the study has some limitations due to the users’ number. Originality/value – The paper uses GRA for drawing the connections between the online social networks reality and its influence to users’ every-day life. Considering the present findings, it can be underlined that the identification of the persons which are influential becomes important in order to get to the proper targeted customers.

scholarly journals Social influence and unfollowing accelerate the emergence of echo chambers

2020 ◽  
Author(s):  
Kazutoshi Sasahara ◽  
Wen Chen ◽  
Hao Peng ◽  
Giovanni Luca Ciampaglia ◽  
Alessandro Flammini ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Mitigation Strategies ◽  
Social Connections ◽  
Online Social Media ◽  
The Social ◽  
Model Dynamics ◽  
Echo Chambers ◽  
Access Information

Abstract While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as “echo chambers.” Here we study the conditions in which such echo chambers emerge by introducing a simple model of information sharing in online social networks with the two ingredients of influence and unfriending. Users can change both their opinions and social connections based on the information to which they are exposed through sharing. The model dynamics show that even with minimal amounts of influence and unfriending, the social network rapidly devolves into segregated, homogeneous communities. These predictions are consistent with empirical data from Twitter. Although our findings suggest that echo chambers are somewhat inevitable given the mechanisms at play in online social media, they also provide insights into possible mitigation strategies.

Indigenous language newspapers and the digital media conundrum in Africa

2021 ◽  
pp. 026666692098340
Author(s):  
Kevin Onyenankeya
Keyword(s):  
Social Media ◽  
Digital Media ◽  
Digital Transformation ◽  
Qualitative Approach ◽  
Indigenous Language ◽  
Technological Determinism ◽  
Traditional Media ◽  
Digital Revolution ◽  
The Future ◽  
Major Factors

The future of journalism is being shaped by the convergence of technology and societal shifts. For indigenous language press in Africa battling to stay afloat amidst stiff competition from traditional media, the pervasive and rapidly encroaching digital transformation holds both opportunities and potential threats. Using a qualitative approach, this paper examined the implication of the shift to digital media for the future of the indigenous language newspaper in Africa and identifies opportunities for its sustainability within the framework of the theories of technological determinism and alternative media. The analysis indicates poor funding, shrinking patronage, and competition from traditional and social media as the major factors facing indigenous newspapers. It emerged that for indigenous language newspapers to thrive in the rapidly changing and technology-driven world they need to not only adapt to the digital revolution but also explore a business model that combines a futuristic outlook with a practical approach.

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