Scrape website content and extract topics

A Project on Temporal Topic Modeling

Data Science and Machine Learning projects

Adapted BERTopic pipeline for Topic Modeling the arXiv dataset

Code relating to work carried out during an internship at Sinch, consisting of an analysis of current topic modeling models.

2023F-Machine Learning Term Project: Topic Modelling on Amazon Review

Topic modeling is a text mining technique in which an algorithm is applied to a large corpus of documents that identifies patterns of word co-occurrence. These patterns of word co-occurrence are conceptualized as “topics” which can be used to discover latent structures in the corpus, to group similar documents together.

LDA, BERTopic and bipartite network for topic modeling

Analysing customer reviews using unsupervised learning approaches via Topic Modelling

Exploring topic modeling techniques, sentiment analysis, and classification algorithms using the Kaggle dataset "Tripadvisor Reviews 2023"

Using BERTopic to show the path of technological advancements in the different phases of the economic cycle (January 2005- January 2023).

Topic modeling on Shopee's 1-star reviews to uncover insights and prevalent topics within the reviews.

Document Clustering, Summarisation and Visualisation on 20NewsGroup

Repository for code and original datasets for MSc Dissertation - University of Sussex 2022

Unveiling Sentiments and Topics in COVID-19 Vaccine Comments on YouTube Over Time: from the First Vaccine Approval to the Post-Pandemic Era

Identify the freedom of a local news outlet by comparing sentiment and stance of published news against international outlets.

A Quotebank data analysis to build a political party classifier based on quotes, explained with a data story. Includes sentiment analysis, grammatical structure/complexity analysis and topic labeling.

Discover 'Yelp Review Scraper', a smart tool that takes your favorite restaurants and serves up insightful summaries based on Yelp reviews. This automated solution goes beyond simple data collection by generating comprehensive summary reports that help you make more informed dining choices.

A machine learning pipeline for detecting Slovenian political bias based on sentiment towards various topics and political parties.