scholarly journals Public Trolling Detection on Twitter Using Machine Learning

2021 ◽  
Vol 9 (VII) ◽  
pp. 3097-3100
Author(s):  
Miss. Pooja Dilip Dhotre
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Social Network ◽  
Social Networking ◽  
Social Networking Sites ◽  
Machine Learning Algorithms ◽  
The People ◽  
The World ◽  
Added Benefit ◽  
Current Popularity

Social media websites are among the internet's most far-reaching digital sites. Billions of social network users exist Users' frequent interactions with social networking sites, like Twitter, have a widespread and sometimes unfortunate effect on day-to-day life. Social networking sites make it easy for large amounts of unwanted and unrelated information to spread around the world. Twitter is a popular micro blogging service where users connect with others with similar interests. Because of the current popularity of Twitter, it is vulnerable to public shaming. Recently, Twitter has emerged as a rich source of human-generated information, with the added benefit of connecting you with customers and enabling two-way communication. It is generally accepted that when someone posts a comment in an occurrence, it is likely to humiliate the victim. The fact that shaming users' follower counts increase faster than that of the people who don't use shame is interesting. Using machine learning algorithms, users will be able to identify disrespectful words, as well as the overall negativity of those words, which is displayed in a percentage.

scholarly journals Rumour Detection Models & Tools for Social Networking Sites

2019 ◽  
Vol 9 (2) ◽  
pp. 3291-3296
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Early Stage ◽  
Economic Losses ◽  
Learning Approaches ◽  
The People ◽  
Social Media Platforms ◽  
Fuzzy Logic Technique

Efficient utilization of social networking sites (SNS) had reduced communication delays, at the same time increased rumour messages. Subsequently, mischievous people started sharing of rumours via social networking sites for gaining personal benefits. This falsified information (i.e., rumour) creates misconception among the people of society influencing socio-economic losses by disrupting the routine businesses of private and government sectors. Communication of rumour information requires rigorous surveillance, before they become viral through social media platforms. Detecting these rumour words in an early stage from messaging applications needs to be predicted using robust Rumour Detection Models (RDM) and succinct tools. RDM are effectively used in detecting the rumours from social media platforms (Twitter, Linkedln, Instagram, WhatsApp, Weibo sena and others) with the help of bag of words and machine learning approaches to a limited extent. RDM fails in detecting the emerging rumours that contains linguistic words of a specific language during the chatting session. This survey compares the various RDM strategies and Tools that were proposed earlier for identifying the rumour words in social media platforms. It is found that many of earlier RDM make use of Deep learning approaches, Machine learning, Artificial Intelligence, Fuzzy logic technique, Graph theory and Data mining techniques. Finally, an improved RDM model is proposed in Figure 2, efficiency of this proposed RDM models is improved by embedding of Pre-defined rumour rules, WordNet Ontology and NLP/machine learning approach giving the precision rate of 83.33% when compared with other state-of-art systems.

scholarly journals Prediction of Fake Tweets Using Machine Learning Algorithms

2021 ◽  
Author(s):  
M. Sreedevi ◽  
G. Vijay Kumar ◽  
K. Kiran Kumar ◽  
B. Aruna ◽  
Arvind Yadav
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Fake News ◽  
Internet Media ◽  
Learning Techniques ◽  
False News

Social networking sites will attract millions of users around the globe. Internet media is becoming popular for news consumption because of its ease, simple access and fast spreading of data takes to consume news from social media. Fake news on social media is making an appearance that is attracting a huge attention. This kind of situation could bring a great conflict in real time. The false news impacts extremely negative on society, particularly in social, commercial, political world, also on individuals. Hence detection of fake news on social media became one of the emerging research topic and technically challenging task due to availability of tools on social media. In this paper various machine learning techniques are used to predict fake news on twitter data. The results shown by using these techniques are more accurate with better performance.

The role of social networking sites in the revolution of 25 January 2011 Egyptian

2019 ◽  
Vol 2 (3) ◽  
pp. 1
Author(s):  
Qassim Alwan Saeed ◽  
Khairallah Sabhan Abdullah Al-Jubouri
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Arab Spring ◽  
The World ◽  
The Revolution

Social media sites have recently gain an essential importance in the contemporary societies، actually، these sites isn't simply a personal or social tool of communication among people، its role had been expanded to become "political"، words such as "Facebook، Twitter and YouTube" are common words in political fields of our modern days since the uprisings of Arab spring، which sometimes called (Facebook revolutions) as a result of the major impact of these sites in broadcasting process of the revolution message over the world by organize and manage the revolution progresses in spite of the governmental ascendance and official prohibition.

scholarly journals Portale społecznościowe w doświadczeniach ośmiolatków

2018 ◽  
Vol 41 (2) ◽  
pp. 100-107
Author(s):  
Małgorzata Dankowska-Kosman ◽  
Iwona Staszkiewicz-Grabarczyk
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Primary Schools ◽  
Online Resources ◽  
The Internet ◽  
Self Presentation ◽  
The World ◽  
The Subject ◽  
Near Future

The subject of considerations are social media in the experience of children aged 8. The methodology selected was the method of focus groups. Focus participants were recruited from forty thirdgrade students from two selected primary schools. The results of the research presented in the text indicate a great interest on the part of the youngest generation in social networking sites. At the same time, they signal that children, despite the systematic use of these portals, are aware of the dangers resulting from applying these tools. Keeping watch of the education of their children, parents very often do not permit their offspring to use online resources unconsciously. Students recognize the risk of making inappropriate acquaintances, the consequences of self-presentation on the Internet, while being curious about the world of young citizens who will join active recipients of social networking sites in the near future.

scholarly journals THE IMPACT OF INSTAGRAM MARKETING ADOPTION TOWARDS CONSUMER PURCHASE DECISION ON FASHION

2020 ◽  
Vol 8 (2) ◽  
pp. 1
Author(s):  
Daniel Augustinus ◽  
Agnes Agnes
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Virtual Communities ◽  
Positive Impact ◽  
Strong Relationship ◽  
Purchase Decision ◽  
Fashion Industry ◽  
The World ◽  
The Impact

Social networking sites have been emerged and transformed the world, bringing the world and its people closer. Social media which are part of social networking sites have become more effective in marketing tools; it helps in creating opportunities and awareness to consumers. Social media platform such as Instagram has recently become the most popular social networking sites among the young people. In addition, selling and market the products in the virtual store on Instagram represents a new shopping mode for most consumers, especially youngsters both men and women, and they represent an important role in influencing fashion consumer purchase decision through social networking sites. This study attempted to investigate impact of social networking sites towards consumer purchase decision on fashion industry. Therefore, questionnaires are spreaded out to 110 respondents who are social media users in Medan in order to gather the necessary information and data. The results of this research, it is concluded that social networking sites (the usability of Instagram) influences and give impact towards consumer purchase decision on fashion. Moreover, both of the variables have a strong relationship on each other and considered to be linear. The results also demonstrate that Instagram influences fashion consumer purchase decision through its usability such as good metrics, eye catching content, and recommendations from others. Furthermore, Instagram is also proved to have a positive impact towards consumer purchase decision by creating awareness, provide satisfaction feeling and creating virtual communities which may motivates consumer to do an online purchase.  

scholarly journals ANALYSIS OF VARIOUS APPROACHES OF ABUSIVE TEXT DETECTION IN ONLINE SOCIAL NETWORKS

2021 ◽  
pp. 124-130
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
English Language ◽  
Research Work ◽  
Accurate Method ◽  
Online Social Networking ◽  
The People ◽  
Language Constructs

Social media is one of the most influential tool for sharing information across different regions among different users .The people sharing their interests in various aspects in online social networking platforms like Facebook, twitter etc. Therefore the usage of hate text steadily increasing. Nowadays it has been reviled unfair behavior of the users in social networking sites. The existence of abusive text on different online social networking platforms and identification of such text is a big challenging task. To understand the complexity of language constructs in different languages is very difficult .Already lot of research work has completed in English language. This paper gives detail analysis of detecting hate text in various languages Hindi, urdu, Arabic, Bengali, Telugu. We incorporated various kinds of ML and DL based algorithms to identify hate text in OSN’s. A review is done related to different classifiers where a comparison made between different models of ML, DL algorithms. Finally finds the accurate method to classify the text is offensive or not by finding the parameters i.e. accuracy and F1score

scholarly journals Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches

2020 ◽  
Vol 17 (4) ◽  
pp. 1328
Author(s):  
Syed Tanzeel Rabani ◽  
Qamar Rayees Khan ◽  
Akib Mohi UD Din Khanday
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Suicidal Ideation ◽  
Social Networking ◽  
Social Networking Sites ◽  
Social Stigma ◽  
Ensemble Methods ◽  
Health Issues ◽  
Mental Health Issues ◽  
The People

Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim of this unfortunate mental disorder. The data is collected from Twitter, one of the popular Social Networking Sites (SNS). The Tweets are then pre-processed and annotated manually. Finally, various machine learning and ensemble methods are used to automatically distinguish Suicidal and Non-Suicidal tweets. This experimental study will help the researchers to know and understand how SNS are used by the people to express their distress related feelings and emotions. The study further confirmed that it is possible to analyse and differentiate these tweets using human coding and then replicate the accuracy by machine classification. However, the power of prediction for detecting genuine suicidality is not confirmed yet, and this study does not directly communicate and intervene the people having suicidal behaviour.

scholarly journals Spam Detection Framework using ML Algorithm

2020 ◽  
Vol 8 (6) ◽  
pp. 5326-5329
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Social Networking ◽  
Information Sharing ◽  
Detection System ◽  
Reliable Data ◽  
Machine Learning Algorithms ◽  
Spam Detection ◽  
Function Type ◽  
Use Of Social Media

The current use of social media has created incomparable amounts of social data, as it is a cheap and popular information sharing communication platform. Nowadays, a huge percentage of people depend on the accessible material on social networking in their choices (e.g. comments and suggestions about a subject or product). This feature on exchanging knowledge with a wide number of users has quickly prompted social spammers to exploit the network of confidence to distribute spam messages and support personal forums, advertising, phishing, scams and so on. Identifying these spammers and spam material is a hot subject of study, and while large amounts of experiments have recently been conducted to this end, so far the methodologies are only barely able to identify spam feedback, and none of them demonstrates the value of each derived function type. In this study, we have suggested a machine learning-based spam detection system that determines whether or not a specific message in the dataset is spam using a set of machine learning algorithms. Four main features have been used; including user-behavioral, user-linguistic, reviewbehavioral and review-linguistic, to improve the spam detection process and to gather reliable data

Social Media as a New Emerging Tool of Marketing

2017 ◽  
pp. 1-10
Author(s):  
Rawan T. Khasawneh
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Social Networking ◽  
Social Networking Sites ◽  
Social Media Marketing ◽  
Network Marketing ◽  
The Third ◽  
Electronic Marketing ◽  
Distinct Features

During the fast growth of social media, the ways companies usually use in their marketing are changed; social networks became a great approach for companies to improve their communication with customers. The wide usage of social networking sites and tools by individuals makes companies want to think carefully on how they can benefit from such usage in rebuilding their relationship with customers and increasing their engagement level. Such companies found that social media marketing is the solution through which companies and their customers will become much closer. This chapter covers three main sections where traditional marketing and electronic marketing concepts are reviewed in the first section. Then a detailed exploration of social networks and their distinct features is presented in the second section. Finally a discussion of social network marketing tools and its related technologies is explored in the third section.

Social Media - A study to explore its Role and Contribution in Promoting Peace

2015 ◽  
Vol 9 (1and2) ◽  
Author(s):  
Mukta Martolia
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Northeast India ◽  
Human Interaction ◽  
Internet Technology ◽  
Religious Groups ◽  
The People ◽  
Use Of Social Media ◽  
The Arab Spring

In today’s world, the internet technology has grown widely, and social media have become a new platform to connect people. We see the use of social media to bridge the divides between different ethnic and religious groups and fostering inter-ethnic dialogues. Recently we have witnessed the Arab Spring, the Jan Lokpal Bill of Anna Hazare, and many such cases that have proved the power of social media. Thus, we can say that this was just the beginning of a wave, an era in the use of social networks to bring people together to fight and protest against violence. The power of social media cannot be ignored today. It has become essential and easy medium to reach a large number of audiences and has become a vital element of today’s life. The social media has proved itself to be a powerful tool for the promotion of peace and has provided not only national but international platform, which allows people to make a positive difference. Social media can be a powerful tool to mobilize people to build peace. With an estimation of around 200 million-plus blogs, more than 120 million YouTube videos and over 500 million Facebook users worldwide, we know that online social networking is a form of human interaction with enormous impact. It is a well-known fact that media affects the minds and behaviors of young people. If media and technology combined together, it can save lives. Thus, the main objective of the study was to evaluate the strength and weaknesses of social media as a tool in facilitating peace in Conflict Situation. The study also tried to analyze and figure out the contribution of social media in promoting peace and preventing violence. For the study various blogs were considered, who were working to bind the people of Northeast India together. Many social networking sites were studied as well to explore many facts.

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