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
2025-06-28 16:30:12 - Adil Khan
Alpha User Acquirer
Project Area of Specialization Artificial IntelligenceProject SummaryCurrently, 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 ObjectivesThis 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.
- 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
- 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 SystemCore Industry ITOther Industries Others Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Decent Work and Economic Growth, Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 77200 | |||
| GPU (GTX 1060) | Equipment | 1 | 32650 | 32650 |
| Twitter Premium API (for 3 months) | Equipment | 3 | 5100 | 15300 |
| Internet Device | Equipment | 1 | 1500 | 1500 |
| Internet for (5 Months) | Equipment | 5 | 1500 | 7500 |
| Cloud Hosting (5 Months) | Equipment | 5 | 2050 | 10250 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |