Inspiration
In Spite of living in a world of technology and opinions, many people feel helpless and in dire need of assistance due to lack of considerate people in their vicinity. Moreover, in the era of social media addiction, platforms like Twitter have become prone to malicious and hate tweets.
What it does
Sashakt - Be Aware, Be Secure is a project aimed at combating the above problem statement through our various features. It includes providing assistance through filing-complaint(via sms), reading and composing blogs, resource pages ( self-defense, quiz pages) and twitter tweet analysis to make them fully aware and equipped in this present world of technology.
How we built it
The features of our project are divided mainly into four domains-:
- Read & Compose Blogs-: Anything can be found provided one looks at the right place. With this idea in mind, we designed the feature of writing small blogs where different people can tell how they managed to cope with their difficulties and stress for others to read and get inspired.
- Send SMS Seeking Help-: This is basically a system where a user can send an sms to our team (after entering their credentials) and file a complaint without letting anyone know. This has been done using sms sending APIs of Vonage (using free credits).
- Twitter Tweet Analysis-: The user can enter any trending hashtag and the website offers an analysis in the form of wordcloud and pie charts. This involves the use of Machine Learning.
- Resource Pages-: We have added resource pages in our project that includes information/videos on self-defense and a small quiz on women safety.
Challenges we ran into
- Had technical setup issue related to sklearn library while developing the project.
- Faced problem while gathering illustrations and graphical representation for the related content of the website.
- Finding free API that met all of our requirements.
- Ran into multiple error while deploying the app.
Accomplishments that we're proud of
- With the project Sashakt, we aimed to create a website that serves as an assistant and offers features of filing complaints, reading blogs and becoming aware of social media atrocities.
- Towards the end of the project, we were able to write working code for all the above mentioned features. The user can login or register, add contacts, write their own blogs, send sms to a number filing any complaint and see the analysis of twitter tweets by entering any trending hashtag.
- We were able to learn various aspects of coding through this project. We worked with python, flask, html, css, bootstrap, Javascript, sqlite, Machine Learning, APIs etc using Visual Studio Code, git and gitHub.
What we learned
• We learnt the front-end of the website which includes the HTML and CSS files handling the user-interface. (design layout,button, Content, images, navigation, and internal linking) • We learnt handling the backend in flask which includes integrating the html files to flask and thus enabling the running of server at localhost. • We learnt the backend for login, register, contacts and blog pages consisting of insertion of rows and authentication of users (in case of login and register). It also includes managing the database (sqlite) and linking it with flask. • We learnt the SMS Sending backend using the Vonage API. It takes inputs from the user and then sends all the details to one number (In our case, the registered mobile number on vonage) from Vonage’s default number. • We made the Machine Learning model for twitter tweet analysis. The first step involves using twitter API to access all the tweets with a particular hashtag taken from the user and then calculating polarity using textblob module in Python. • We displayed the charts on the flask browser using chartjs.
What's next for Sashakt
Although the project greatly covers our targets, there are still further alterations that we would like to do to make the website even better. • Adding the feature of having a profile-picture, bio, updating account and editing blogs. • Adding blog recommendations based on likes and topics. • Segregation of the SMS messages received based on complaint-category. • Adding an emergency SOS feature to all the contacts entered by the user. • Sentiment Analysis of text entered by users along with tweet analysis.
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