Design and Development of Software for detection of antistate actors based on Tweet Data Anaytics
The use of social networking sites (also known as microblogs) has increased to such an extent that they have become most widely used medium of communication all over the world. People use microblogs for sharing experiences of their life, sentiments, ideas and opinions about the happenings going on a
2025-06-28 16:31:26 - Adil Khan
Design and Development of Software for detection of antistate actors based on Tweet Data Anaytics
Project Area of Specialization Cyber SecurityProject SummaryThe use of social networking sites (also known as microblogs) has increased to such an extent that they have become most widely used medium of communication all over the world. People use microblogs for sharing experiences of their life, sentiments, ideas and opinions about the happenings going on around them. Twitter is the famous microblogging service having more than 1 billion active users. Twitter users post them opinions in tweets containing limited words. These tweets are a great source of feedback for any product/service providers to improve marketing. Some people or groups post hate speech messages on twitter in order to spread extremism and suspicious anti-state activities.The tweets are mostly written in informal language and broken spellings that make their analysis a challenge.Most of the times the message conveyed by the tweets is vague that makes it difficult to understand the real opinion stated by the elementary computational models. The need for detection of sentiments and opinions expressed in messages/tweets automatically, introduced a research field known as sentiment analysis. Text sentiment analysis includes the use of computational powers to understand the sentiment inferred in the text. Sentiment analysis can be applied to analyze the suspicious activities done by different terrorist organizations as well as other individuals.This project will create an opportunity to detect the terrorists’ tweets and those having hatred speech along with the usernames with the help of convolutional neural network. The main objective of this project is to prevent internet crimes by designing a model for recognizing those user groups who are involved in suspicious doings.The system will detect the sentiments of tweets and analysis the radical views of the users. We aim to detect the twitter users involved in promoting terror related anti state activities and propagating their agenda based on radical mindset.The system will be helpful for the law enforcement agencies for the recognition of the suspicious antis-state activities.System takes the tweets of the twitter user and detect the radical and extremist tweets through hashtag and keywords.The system stores the tweets in database and perform sentiment analysis through different learning algorithms including Naive Bayes,Random forest,KNN.System will collect tweets in a real time from the twitter live stream based on specified hashtags.Then it will store the formatted tweets in database.Sentiment analysis will be performed Sentiment on the tweets stored in the database to classify their nature i.e pro-state and anti-state.In this a network of people having antistate agenda on Twitter will be exposed to law enforcement agencies.
Project ObjectivesThe main objective of this project is to prevent Twitter crimes by designing a model for recognizing those user groups who are involved in suspicious anti-state doings.The system will detect the sentiments of tweets and analyse the anti-state views of the users. We aim to detect the twitter users involved in promoting terror related anti state activities and propagating their agenda based on radical mindset.The system will be helpful for the law enforcement agencies for the recognition of the suspicious anti-state activities.
Project Implementation MethodThe system will detect the sentiments of tweets and analysis the antistate views of the users.System takes the tweets of the twitter user and detect the radical and extremist tweets through hashtag and keywords.The system stores the tweets in database and perform sentiment analysis through different learning algorithms including Naive Bayes,Random forest,KNN.System will collect tweets in a real time from the twitter live stream based on specified hashtags.Then it will store the formatted tweets in database.Sentiment analysis will be performed Sentiment on the tweets stored in the database to classify their nature i.e pro-state and anti-state.Following are the implementation constraints of systm:
- The system read the labeled tweets as pro-state and anti-state.
- The system remove all non-letters form the tweets.
- The system classify the tweets as pro-state and anti-state.
- The system display the anti-state tweets of each user sprading hatred on Twitter.
- The system will cluster the anti-state users as potential threat to state.
- In this way a network of people having antistate agenda on Twitter will be exposed to law enforcement agencies.
This Automated Surveillance System on Twitter will serve many benefits including social,political,economical and technological.
Social benefit:- Early detection of Tweets will bring the safety of people by ensuring the proactive approach. This system will bring an awareness among Twitter users to be vigilant about any suspicious activity and their interaction on social media.
Political benefit: Surveillance system will bring a proactive approch by state agencies which will ensure peace in the country.National stability will ensure political stability in a country and will create a stable environment for the growth of democracy.
Economical benefit: This system has only one time expense for development.Later on it can be used freely by authorized state institutions. Through frequent surveillance of antistate activities,terror related activites will be reduced and eventually trade market will grow bringing an economic stability and foreign investment.
Technological benefit: This Automated Surveillance System on Twitter can be enhanced on further platforms by developing on other social media platforms. Machine Learning Algorithms can further by developed by enhancing functionality of a system.
Automated Surveillance System is the final delieverable of project which is developed by using the techniques in the following domain:
Machine learning
Artificial intelligence
Web engineering
Final Deliverable of the Project Software SystemCore Industry SecurityOther Industries IT Core Technology Big DataOther Technologies Artificial Intelligence(AI)Sustainable Development Goals Decent Work and Economic Growth, Peace and Justice Strong InstitutionsRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 18000 | |||
| Hard drive (400GB) | Equipment | 1 | 8000 | 8000 |
| APIs Key for data extraction imply payment | Miscellaneous | 1 | 10000 | 10000 |