Interest Miner is a cutting-edge platform designed to revolutionize academic research by harnessing the power of machine learning to analyze users' interests.

By pulling data from Twitter and scholarly research papers, Interest Miner provides scholars with valuable insights into trending topics, correlations between interests, and long-term interest trends.

Challenge

Academic scholars often struggle to keep pace with emerging trends and topics relevant to their research areas.

With an overwhelming amount of data available online, identifying key interests and understanding their correlations poses a significant challenge.

Interest Miner sought to address this challenge by developing a platform that could efficiently extract, analyze, and visualize data from Twitter and scholarly research papers to provide actionable insights to scholars.

Interest Miner's innovative solution involved several key components:

1. API Integration: Integration with Twitter and scholarly databases to pull data on tweets and research papers, spanning the past six months.

2. Keyword Analyzer: Advanced keyword analysis algorithms to segment users' interests based on topics extracted from tweets and research papers.

3. Data Models: Data models designed to capture short-term and long-term interest trends of users, providing valuable insights into evolving research interests.

4. Metrics Comparison: Metrics comparison feature enabling scholars to compare the interests of two users, identifying commonalities and differences.

5. Visualization: A suite of over eight dynamic charts to visualize extracted data, including trend analysis, correlation maps, and topic clusters.

The implementation of Interest Miner yielded remarkable results for academic scholars:

- Enhanced Research Insights: Scholars gained access to valuable insights into trending topics and correlations between interests, enabling them to stay informed and adapt their research focus accordingly.

- Improved Decision-Making: By visualizing data trends and comparing interests between users, scholars could make more informed decisions about their research directions and collaborations.

- Time Savings: Interest Miner's automated data extraction and analysis capabilities saved scholars significant time and effort, allowing them to focus more on their research and less on data collection and analysis.