scholarly journals Identifying System Location Specifics based on Classification of Worldwide Tweets

2019 ◽  
Vol 8 (12) ◽  
pp. 5452-5454
Keyword(s):  
Social Networking ◽  
Real Time ◽  
Monitoring System ◽  
Social Networking Sites ◽  
Performance Metrics ◽  
Spatiotemporal Analysis ◽  
Cyber Crime ◽  
Fake News ◽  
Digital Form

As social networking sites are gaining populism across the globe, people are more enthusiastic about sharing their thoughts on Various networking Platforms. Facebook and Twitter have become a leading destination for sharing various kinds of information. In the existing literature the focus is to access the information published in the networking platforms in the real-time, and they do not focus on obtaining the geo-location of the user. Here we propose a monitoring system that classifies the tweets using some reliable techniques which can be used across the globe without any security concerns. As there is a lot of fake news available in the digital form, there is a definite need to access the user information and his geo-location metrics. In this paper, we have introduced Naive Bayes Multinomial classifier and a few other models which performs a spatiotemporal analysis. This study also identifies a comprehensive set of performance metrics which can access the tweet’s country of origin by using eight tweet-inherent features. The outcome of this analysis can be used by various cyber-crime departments to deal with the numerous cybercrime cases on networking platforms, and real-time decisive actions can be taken.

Online Abuse

2012 ◽  
pp. 911-917 ◽  
Author(s):  
Adam M. Bossler ◽  
Thomas J. Holt
Keyword(s):  
Social Networking ◽  
Real Time ◽  
Social Networking Sites ◽  
Text Messaging ◽  
Cell Phones ◽  
The Internet ◽  
Online Harassment ◽  
Online Abuse ◽  
Beneficial Impact

The development of computers, cell phones, and the Internet allows individuals to connect with one another with ease in a variety of ways in near real time. The beneficial impact of these resources, however, has been adulterated by some to engage in abusive communications while online. Specifically, individuals now use email, text messaging, and social networking sites to spread hurtful or malicious information about others. This entry summarizes the problem of online abuse via cyberbullying, online harassment, and stalking by discussing the prevalence of these phenomena as well as the prospective predictors of victimization.

Understanding the Landscape of Online Deception

2021 ◽  
pp. 39-66
Author(s):  
Hicham Hage ◽  
Esma Aïmeur ◽  
Amel Guedidi
Keyword(s):  
Social Networking ◽  
Information And Communication Technologies ◽  
Social Networking Sites ◽  
Communication Technologies ◽  
Fake News ◽  
New Information ◽  
Global Issue ◽  
Information And Communication ◽  
Online Deception ◽  
Major Factors

While fake and distorted information has been part of our history, new information and communication technologies tremendously increased its reach and proliferation speed. Indeed, in current days, fake news has become a global issue, prompting reactions from both researchers and legislators in an attempt to solve this problem. However, fake news and misinformation are part of the larger landscape of online deception. Specifically, the purpose of this chapter is to present an overview of online deception to better frame and understand the problem of fake news. In detail, this chapter offers a brief introduction to social networking sites, highlights the major factors that render individuals more susceptible to manipulation and deception, detail common manipulation and deception techniques and how they are actively used in online attacks as well as their common countermeasures. The chapter concludes with a discussion on the double role or artificial intelligence in countering as well as creating fake news.

#CleftProud

2018 ◽  
Vol 55 (10) ◽  
pp. 1339-1349 ◽  
Author(s):  
Nicola Marie Stock ◽  
Anna Martindale ◽  
Claire Cunniffe
Keyword(s):  
Social Networking ◽  
Real Time ◽  
Emotional Support ◽  
Social Networking Sites ◽  
Online Survey ◽  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Dental Health ◽  
Time Data ◽  
Real Time Data

Background: More than 2 billion people worldwide now use social networking sites, with an increasing number of users accessing these sites to obtain health information and engage in emotional support. Yet, investigation of social networking sites in the context of cleft lip and/or palate (CL/P) has been scarce. Methods: Real-time data posted during 2 weeks in April 2017 were collected from 2 existing private Facebook groups (hosted by the Cleft Lip and Palate Association United Kingdom) using video screen capture software. The number of posts, comments, unique contributors, and post “likes” was recorded, as well as the type and theme of each post. Data relating to the benefits and challenges of participation in the 2 groups were also collected via an online survey. Results: A content analysis of real-time data identified perioperative care, associated syndromes, and dental health to be particular areas of concern for parents/caregivers. Expectations, experiences, and outcomes of further treatment were key topics of discussion for adults with CL/P. Common benefits of the groups included the ability to connect with others, learn about local events, give and receive emotional support, and obtain quick responses to queries in a semi-anonymous environment. Disadvantages of the groups included a reliance upon opinion rather than medical fact and the frequent use of inappropriate terminology. Conclusions: Social networking sites appear to be a helpful source of health-related information and peer support for the CL/P population, yet closer monitoring of these groups may be required.

scholarly journals An Enhanced Sybil Guard to Detect Bots in Online Social Networks

2021 ◽  
Author(s):  
Nisha P. Shetty ◽  
Balachandra Muniyal ◽  
Arshia Anand ◽  
Sushant Kumar
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Networking ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Easy Access ◽  
Classifier Combination ◽  
Fake News ◽  
Wide Scale ◽  
Set Up

Sybil accounts are swelling in popular social networking sites such as Twitter, Facebook etc. owing to cheap subscription and easy access to large masses. A malicious person creates multiple fake identities to outreach and outgrow his network. People blindly trust their online connections and fall into trap set up by these fake perpetrators. Sybil nodes exploit OSN’s ready-made connectivity to spread fake news, spamming, influencing polls, recommendations and advertisements, masquerading to get critical information, launching phishing attacks etc. Such accounts are surging in wide scale and so it has become very vital to effectively detect such nodes. In this research a new classifier (combination of Sybil Guard, Twitter engagement rate and Profile statistics analyser) is developed to combat such Sybil nodes. The proposed classifier overcomes the limitations of structure based, machine learning based and behaviour-based classifiers and is proven to be more accurate and robust than the base Sybil guard algorithm.

scholarly journals Evaluating the Spread of Fake News and its Detection. Techniques on Social Networking Sites

2020 ◽  
Vol 22 (1) ◽  
pp. 111
Author(s):  
Isyaku Hassan ◽  
Mohd Nazri Latiff Azmi ◽  
Akibu Mahmoud Abdullahi
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Fake News ◽  
The Public ◽  
Detection Techniques ◽  
Literature Synthesis ◽  
Social Media Platforms ◽  
The Creation ◽  
Linguistic Approach

The phenomenon of fake news has become a much contentious issue recently. The controversy regarding this issue has further been intensified by the openness of social media platforms. Via a systematic review, this paper offers a discussion on the spread and detection techniques of fake news on Social Networking Sites (SNSs). A total of 47 articles eventually fulfilled the inclusion criteria and were coded for the literature synthesis. The overall findings from the literature on fake news and social media have been extracted and synthesized to explore the creation, influence and popular techniques and dimensions used for fake news detection on SNSs. The results showed that various entities are involved in the creation and spread of fake news on SNSs, including malicious social and software agents. It was also found that early registered users, old people, female users, delusion-prone persons, dogmatic persons, and religious fundamentalists are more likely to believe in fake news than other groups of individuals. One of the major problems of the existing techniques is their deficiency in datasets. Therefore, future studies on fake news detection should focus on developing an all-inclusive model with comprehensive datasets. Social media users require fake news detection skills especially using linguistic approach. This study provides the public with valuable information about the spread and detection of fake news on SNSs. This is because SNSs are an important avenue for fake news providers.

scholarly journals Identification and Classification of Cyberbully Incidents using Bystander Intervention Model

2019 ◽  
Vol 8 (2S4) ◽  
pp. 1-6
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Online Community ◽  
Semantic Analysis ◽  
Bystander Intervention ◽  
Intervention Model ◽  
Alert Message ◽  
Random Decision Forest ◽  
Decision Forest

Cyberharassment is bullying and degrading the adults by means of posting the comments like hurtful and derogatory humor over the internet in an online community. Though few bystanders ever try to reduce the conflicting effects of cyberbullying, and bystanders ever endeavor to interrupt. This will analyze the chattels of articulatory study on bystander intervention using the caricatured procedural made online Social Networking Sites. The proposed works mainly focus on the analysis of direct intervention by bystanders. The direct intervention allows bystanders to do reporting and blocking of cyberbully activities as additional features here. It will generate a report which contains the details of bully by means of alert message and block that bully by the bystander with the victim’s permission in the Facebook. This proposed framework will detect cyberbully words from the short hand text and emoticons on the comment sections using Latent semantic analysis (LSA). The Cyberbully words will be classified using a Random Decision Forest algorithm.

scholarly journals Review On: Detection of Spam Comments Using NLP Algorithm

2018 ◽  
Vol 7 (01) ◽  
pp. 23386-23489
Author(s):  
Miss Rohini D.Warkar ◽  
Mr.I.R. Shaikh
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Natural Language Processing ◽  
Natural Language ◽  
Social Networking ◽  
Real Time ◽  
Social Services ◽  
Language Processing ◽  
Social Networking Sites ◽  
Online Media

Detecting trending topics is perfect to summarize information getting from social media. To extract what topic is becoming hot on online media is one of the challenges. As we considering social media so social services are opportunity for spamming which greatly affect on value of real time search. Therefore the next task is to control spamming from social networking sites. For completing these challenges different concepts of data mining will be used. For now whatever work has been done is narrated below like spam control using natural language processing for preprocessing and clustering. One account has been created for making it real.

Understanding the Landscape of Online Deception

2020 ◽  
pp. 290-317
Author(s):  
Hicham Hage ◽  
Esma Aïmeur ◽  
Amel Guedidi
Keyword(s):  
Social Networking ◽  
Information And Communication Technologies ◽  
Social Networking Sites ◽  
Communication Technologies ◽  
Fake News ◽  
New Information ◽  
Global Issue ◽  
Information And Communication ◽  
Online Deception ◽  
Major Factors

While fake and distorted information has been part of our history, new information and communication technologies tremendously increased its reach and proliferation speed. Indeed, in current days, fake news has become a global issue, prompting reactions from both researchers and legislators in an attempt to solve this problem. However, fake news and misinformation are part of the larger landscape of online deception. Specifically, the purpose of this chapter is to present an overview of online deception to better frame and understand the problem of fake news. In detail, this chapter offers a brief introduction to social networking sites, highlights the major factors that render individuals more susceptible to manipulation and deception, detail common manipulation and deception techniques and how they are actively used in online attacks as well as their common countermeasures. The chapter concludes with a discussion on the double role or artificial intelligence in countering as well as creating fake news.

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