Text Mining of 5 Million Tweets, a Python Approach | Part 2

Lets continue where we left of with our analysis of remote working peoples’ tweets :)

Please check Part 1 in case you missed it.

The Timeless Walk © Julian Cani

Reason is powerless in the expression of love | Rumi

To perform such analysis, we have employed a combination of topic modeling and also sentiment analysis. For the topic modeling task the algorithm used is LDA, while for the task of sentiment analysis we keep a consistency in using VADER sentiment analysis. The data used for this task has an extra column called “created_at”.

LDA Topic Modeling

LDA uses a probability model where the main idea…


Text Mining of 5 Million Tweets, a Python Approach | Part 1

Credits to iKubINFO, Largest Software Development Company in Albania for supporting this work.

COVID-19 pandemic outbreak required countries to impose urgent domestic and foreign restrictions. Measures to control the spread of the virus to avoid overloading of the hospital care capacity required changes in the overall work system in multiple countries across the globe. As a result of the government measures many companies were required to shift from the “traditional office” to “home office” working environment, thus challenging both employees and organizations.

To understand the effects of the sudden change, in this tutorial, we will perform extraction and analysis of…


In this guide we will have a look at the property market of Tirana, Albania. The article will present a guide of web-scrapping using python and to perform exploratory data analysis, thus extracting valuable insights from raw data.

About 5520 Apartments’ (On sale and for rent) data were extracted from Century21’s website. These data are property of Century21st and can only be taken with authorization (which I have), the purpose of this study is purely educative so please make an ethical use of this guide and always ask for authorization when scrapping data from other websites.

Memories by H. Tocilla

You are not a…


Topic Modeling, Sentiment Analysis & Hate Speech Detection Models using Python

Many are those claiming that the light of scientific and technological revolution will diminish the presence of religion in human life. Yet, it is 2020, and one thing seems inevitable, religion is still here and is here to stay! That being said, it is worth investigating the public opinion towards religion in modern times.

This article presents a comprehensive guide of using Python to extract, pre-process, and analyze tweets about religion. The analysis is about implementing Topic Modeling (LDA), Sentiment Analysis (Gensim), and Hate Speech Detection (HateSonar) models. The step-by-step tutorial is presented below alongside the code and results.

Credits…

Hurmet Noka

Master in Data Science | Works as Software Developer Python | IKubINFO

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