Sentiment Analysis

We gathered a total of 1,515 news articles concerning suicide, building jumps, and related incidents from 2019 to 2024. Utilizing sentiment analysis tools, we categorized the data into two groups: positive sentiment words and negative sentiment words. Our primary objective was to examine the relationship between negative sentiment words and other associated terms.

Categories:
147 Views

Data were collected through the Twitter API, focusing on specific vocabulary related to wildfires, hashtags commonly used during the Tubbs Fire, and terms and hashtags related to mental health, well-being, and physical symptoms associated with smoke and wildfire exposure. We focused exclusively on the period from October 8 to October 31, aligning precisely with the duration of the Tubbs Fire. The final dataset available for analysis consists of 90,759 tweets.

Categories:
323 Views

This data collection focuses on capturing user-generated content from the popular social network Reddit during the year 2023. This dataset comprises 29 user-friendly CSV files collected from Reddit, containing textual data associated with various emotions and related concepts.

Categories:
2062 Views

Supplementary material for article "A Group Decision-Making Method Based on the Experts’ Behaviour During the Debate". Two files containing the comments provided by four expert during a debate to select the best product.

Categories:
88 Views

SART contains 3000 tweets labelled with respect to the polarity of the sentiment expressed: positive, negative or neutral. Each class contains 1300 tweets and the dataset is split into train/validation/test csv files.

Categories:
21 Views

Air travel is one of the most used ways of transit in our daily lives. So it's no wonder that more and more people are sharing their experiences with airlines and airports using web-based online surveys. This dataset aims to do topic modeling and sentiment analysis on Skytrax (airlinequality.com) and Tripadvisor (tripadvisor.com) postings where there is a lot of interest and engagement from people who have used it or want to use it for airlines.

Categories:
706 Views

Companion data of the paper "Using social media and personality traits to assess software developers’ emotions" submitted to the IEEE Access journal, 2022. This dataset contains the anonymized dataset used in the study, including the answers of demographic survey, the answers to the Big Five Inventory, the experiment protocol, the manual analysis from psychologists and participants, all generated charts and data analysis.

Categories:
409 Views

Pages