Janjanam A.

Key Skills

Software

No software listed

Top Subject Matter

Election sentiment analysis using real-time Twitter data (location-based NLP)

Top Data Types

Text

Top Task Types

Entity (NER) Classification

Freelancer Overview

Research Paper: Developing a Location-Based Election Sentiment Analysis Model. Core strengths include Power BI, TensorFlow, and scikit-learn. Education includes Bachelor of Technology, KL University. AI-training focus includes data types such as Text and labeling workflows including Entity (NER) Classification.

Labeling Experience

Research Paper: Developing a Location-Based Election Sentiment Analysis Model

TextEntity (NER) Classification

Developed an election location-based sentiment analysis system using real-time Twitter election text data. Applied NLP preprocessing such as tokenization, stop-word removal, and lemmatization to prepare the dataset for modeling. Used TF-IDF vectorization and multiple classifiers (Naïve Bayes, SVM, Decision Tree, and CNN) to predict sentiment labels for regional trends. • Labeled/annotated sentiment targets implicitly via supervised learning outcomes from labeled data • Computed and evaluated model accuracy to validate label performance • Visualized regional sentiment trends using Power BI dashboards • Reported highest achieved classification accuracy of 81.11% with SVM

2024 - 2024

Education

Work History