ENVIRONMENT: An Investment company is searching for a talented and driven Data Scientist to join their innovative and growing team based in Durbanville, Cape Town. This is an exciting opportunity to ...

In 2026, trading is no longer just about charts, instincts, or financial experience. The real competition in the market has ...

To fine-tune our model, our team manually labeled the sentiment of 3600 tweets and then augmented our data set through back-translation. Text sentiment for each social media platform was then ...

In today's hyperconnected world, social media has become a critical channel for businesses to understand consumers. While social listening tools are widely used, they often fall short, providing only ...

In this tutorial, I will guide you on how to detect emotions associated with textual data and how can you apply it in real-world applications. Understanding emotions associated with text is commonly ...

Have you ever wondered how businesses sift through mountains of customer feedback to uncover what truly matters? Imagine receiving hundreds, if not thousands, of ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Python is a popular programming language extensively used in various applications including Natural Language Processing (NLP). Sentiment analysis, a frequent NLP task, aids in understanding the ...

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...

The analysis pipeline was implemented using Python’s Natural Language Toolkit, Gensim, and scikit-learn libraries, with hyperparameter tuning to maximize model performance. Results: Sentiment analysis ...