Name: Social Media Sentiments: Putin&Carlson Interview💡
Creator: Kaggle
License: https://opendatacommons.org/licenses/by/1-0/index.html

About this Dataset

Social Media Sentiments: Putin&Carlson Interview💡

Dataset Description

Overview:

This dataset encapsulates a comprehensive collection of public sentiments expressed through comments on a pivotal interview featuring Vladimir Putin and Tucker Carlson. The conversation, set against the backdrop of a tumultuous global economy and the critical discourse surrounding Putin's maneuvers in Ukraine, offers a deep dive into the reasons and viewpoints presented by the Russian leader. With over 100,000 comments, this dataset not only reflects diverse global perspectives but also serves as a mirror to the world's reaction to key international events discussed in the interview.

Data Science Applications:

Natural Language Processing (NLP): Utilize advanced NLP techniques, such as sentiment analysis, topic modeling, and emotion detection, to uncover underlying patterns and sentiments. Tools like BERT and GPT can offer nuanced insights into public opinion and discourse trends.
Machine Learning: Employ machine learning algorithms to classify comments, predict sentiment scores, and analyze engagement metrics, providing a quantitative understanding of viewer reactions.
Data Visualization: Create compelling visualizations to represent sentiment distributions, temporal trends in comment activity, and correlations between engagement metrics and sentiment.

Column Descriptors:

Comment: The textual content of the user's comment.
Anonymized Author: A SHA-256 hashed representation of the comment author's username to ensure privacy.
Published At: Timestamp indicating when the comment was posted.
Likes: The number of likes a comment received.
Reply Count: The number of replies to the comment.

Ethically Mined Data:

This dataset was ethically sourced, respecting user privacy and adhering to platform guidelines. Personal identifiers have been anonymized to maintain confidentiality.

Acknowledgments:

We extend our gratitude to YouTube for facilitating an open platform where such vibrant discussions can take place and to the data science community for providing the tools and methodologies that enable this analysis.

Special Note to Data Scientists:

As data scientists, we approach this dataset with neutrality, aiming to extract insights without bias. Our role is to analyze and interpret the data impartially, contributing to a broader understanding of public sentiment on significant global issues. Let's harness this opportunity to showcase the power of data science in illuminating the complexities of human discourse.

Tables

Putin Tucker

@kaggle.kanchana1990_social_media_sentiments_putin_and_carlson_d36c8f54.putin_tucker

6.7 MB
100,000 rows
5 columns

CREATE TABLE putin_tucker (
  "comment" VARCHAR,
  "anonymized_author" VARCHAR,
  "published_at" TIMESTAMP,
  "likes" BIGINT,
  "reply_count" BIGINT
);