Adil Khan 9 months ago
AdiKhanOfficial #FYP Ideas

Alpha User Acquirer

Currently, there are 330 million accounts on Twitter. According to recent surveys, Twitter still has less personal information of users than other social media platforms. Due to this con, its arduous task to gather information from Twitter. But still Twitter has evolved itself as a huge pool of data

Project Title

Alpha User Acquirer

Project Area of Specialization

Artificial Intelligence

Project Summary

Currently, there are 330 million accounts on Twitter. According to recent surveys, Twitter still has less personal information of users than other social media platforms. Due to this con, its arduous task to gather information from Twitter. But still Twitter has evolved itself as a huge pool of data in the form of short status, news updates, links, and announcements that a marketer can promote their brand effectively on this huge platform. But there are still traditional practices ongoing in terms of marketing such as paid ads. Our solution gives another dimension to social marketing by finding and marketing through alpha users by using AI and DataScience. Among the millions of users, there’s a plunge pool of users called alpha users. They have large number of active and effective audience base that helps the content to multiply the audience and reach effectively to the required users. Such people include world top celebrities around the globe. The content of alpha users or influencers is divided into micro-networks, observed through Convolutional Neural-Networks by using AI and their content is also being observed by their indirect followers. There’s no such system available right now that can target brands according to the relevant alpha users using AI. The purpose of our project is to find relevant alpha users through the content posted by them.

Project Objectives

This project will provide a Web based system to users. Objectives of Alpha User Acquirer are:

• Using data science techniques to fetch and pre-process the data.

• Harness the power of AI & Convolutional Neural Networks to find and analyze Alpha Users against a query.

• Ranking & Suggesting Alpha users that may be beneficial for promoting a product or service.

• Using the powerful Django framework to design frontend for naïve users.

Project Implementation Method

“Alpha User Acquirer” allows users to search and analyze influencers via username (if you already know an influencer) or via search term (if you don’t). When users make a query API authentication request is sent to Twitter. Once the request is approved, we start streaming live data from twitter repository and save it on our server/machine. For search terms we extract top 100 users and then extract the most recent 100 tweets and extract the tweet text. For username we simply fetch the latest 100 tweets and extract the text. Then we start cleaning the text, remove useless signs, bad words and stopwords (the, that, for, and etc). Then we remove hyperlinks and hash sign (#). Once the data is clean, we do NER and find top 10 most frequently used terms. Then we use Artificial Intelligence and Convolutional Neural Network to perform basic filtering based on the content extracted from tweets and compare the terms with our query using cosine similarity function. Once we have sorted and filtered the top 10 best relevant influencers, we use our algorithm designed to filter the influencers further based on their following count, activity and interaction with other users. The final output is an influencer which may be best for your campaign.

Flow Chart (Click to Open)

Benefits of the Project

  • Can be extended for educational, economical & political research
  • Will create a new dimension in the field of marketing using Artificial Intelligence
  • Useful in brand influencing
  • Useful in finding new and already existing influencers with the help of content analyzing methods using Data Science
  • Can give direction to newly built businesses or brands
  • Can search influencers on the base of hashtags, usernames or geographical areas

Technical Details of Final Deliverable

  • 1. Connecting with twitter for API authentication and fetching live tweets from Twitter Repository. Do the pre-processing and clean the text for further analysis.
  • 2. Do “Named Entity Recognition” and find the top 10 most frequently used terms using AI. Match the terms with the user query using CNN (Convolutional Neural Network) and filter out relevant alpha users.
  • 3. Filter the alpha users further using the “Algo 9” and find the users that may be beneficial for promoting our product or service.
  • 4. Connect all the modules to the front end & create an interface for naive users so that they can use the platform easily.

The platform will be open for public use free of cost so everyone can benefit from the project. The transferred outcome is a list of alpha user(s) that may prove beneficial for marketing campaign.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Others

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Decent Work and Economic Growth, Industry, Innovation and Infrastructure

Required Resources

Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
GPU (GTX 1060) Equipment13265032650
Twitter Premium API (for 3 months) Equipment3510015300
Internet Device Equipment115001500
Internet for (5 Months) Equipment515007500
Cloud Hosting (5 Months) Equipment5205010250
Miscellaneous Miscellaneous 11000010000
Total in (Rs) 77200
If you need this project, please contact me on contact@adikhanofficial.com
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