Twitter analytis download torrent

Github troll tweets Type- Russian troll tweets. All the datasets are readily downloadable in CSV format. Github scraped public tweets Type- Miscellaneous public tweets. Link- archive. NZ Reddit data set Type- Reddit comments data set. Link- mega. The file size is about GB compressed and over 1 TB uncompressed.

The link provided is of the torrent file which can be easily downloaded using a torrent client. Kaggle customer support data sets Type- Customer support tweets. This can be used in understanding conversational models, and for the study of modern customer support practices and impact. Link- followthehashtag. Just click on the link to browse the datasets.

Lionbridge Type- Miscellaneous. Link- lionbridge. Just click on the link and browse through the list of their available datasets. Link- academictorrents. The link will take you to the Torrent file which can be easily downloaded through a torrent client. Sentiment Type- Tweet sentiment analysis data. Link- help. It filters through the tweets by understanding the negativity or positivity of the tweet or comment by analyzing emoticons. Docnow Type- Miscellaneous. If you would like to turn these tweet identifier data back into the original JSON format then first download the data sets and then use the Hydrator desktop application, or Twarc if you are comfortable working at the command line.

Harvard dataverse Type- USA presidential election tweets. Link- dataverse. Dfreelon Type- Miscellaneous. Head over to the link to find the list of the 45 keywords and download the data. Kaist Type- Miscellaneous public tweets. Link- an. It was used in a study to identify trending topics, identify influencers, rank profiles based on the size of followers or retweets and, analyze temporal behavior along with user participation.

The data was accumulated to conduct a study aimed at visualizing the media landscape, discovering topic authorities, crowd-sourced opinions, identifying topical content, and characterizing information trade on Twitter.

Sentiment Type- Miscellaneous public tweets Link- help. Its file is available in ExcelCSV format and is divided into six fields tweet id, date of the tweet, popularity of the tweet, the query LyX , the user that tweeted and, the text of the tweet. Thinknook Type- Miscellaneous Tweets Link- thinknook. The data is available in. First: date and time, second: tweet, and third: sentiment score for the tweet. The dataset contains a total of 56 million tweets from 3. Through a series of regular expressions, relevant information such as user, movie, and rating is extracted.

The ratings are then cross-referenced with the IMDB page to provide the genre metadata. XnBrPS2B0cS The Twitter dataset contains Twitter interactions related to German politicians of influential political parties for several months in the pre-phase of the German election campaigns The dataset comprises raw data of more than , active users generating more than 1,, tweets. Each one is identified by the ID which helps to pull the tweet out of the stream and get information about the text content, GPS information if it is available , location, and time.

The label for each tweet in the collection comes after the event detection phase is complete. The Baths of Diocletian Twitter account must tweet all-important or potentially hazardous information on the incident in Rome. The data was collected for research, history, testing, and memory. The dataset contains 20, rows, each with a user name, a random tweet, account profile and image, location, and even link and sidebar color.

The Twitter dataset was amassed for research, history, testing, and memory. The tweets were amassed to perform sentiment analysis, contributors were asked to classify positive, negative, and neutral tweets followed by categorizing negative reasons.

The data collection process started in July and ended in December The study aimed at creating training data for classifying racist, sexist, or any kind of hate speech. These rumors are associated with 9 different breaking news.

It was created to perform an analysis of social media rumors and contains Twitter conversations that were initiated by a rumourous tweet.

It was accumulated to analyze the sentiments of users surrounding Apple INC. The dataset contains tweets captured around the first debate on September 21, The tweets collected are from March and April. The dataset contains tweets from all languages but the prevailing languages are English, Spanish, and French. It includes over ,, unique tweets.

It also has a cleaned version of the dataset with ,, unique tweets. The files contain the distribution of tweets collected for the AIDR system, which comes with the geo-coordinated from Twitter. The dataset was gathered to perform a Twitter sentiment analysis to identify patterns of disinformation and unusual propagation of content on Twitter.

The dataset was amassed to perform a sentiment analysis and analyze the emotions of the users. The dataset was gathered between March and July of The data collection was started on May 20, , and is updated every week. The dataset is released for non-commercial research use. It contains over 3.

The data set was released as a challenge for data scientists looking to get started in Natural Language Processing. The dataset contains pre-processed tweets that have been categorized into positive, negative, and neutral categories.

The categorization of tweets is done using emoticons. The Twitter data was accumulated between 15th October-4th November The dataset contains over , tweets accumulated using Twitter API between The tweets were gathered to identify topics that Tesla mostly tweets about. This dataset contains over 70, tweets related to the hashtag posted between 7 th and 11 th January It was accumulated to perform sentiment analysis on tweets concerning the corresponding stocks.

The dataset was used in academic research of traffic accident detection and real-time traffic modeling. The dataset was compiled to train sentiment analysis models and the tweets are classified into positive, negative, and neutral categories. Some of those are hydroxychloroquine, coronavirus, US political tweets, etc. The tweets were posted by 1. It was accumulated to identify Twitter bots. The tweets were gathered between October and March It was accumulated to analyze the sentiments of users towards nuclear energy.

It was used to construct sentiment profiles on publicly traded companies. The data was collected in a time span of almost 5 years is between January November It also offers a cleaned version of the data that excludes retweets and provides over 20 million unique tweets. The dataset was collected between January and March The tweets are divided into two categories; Positive: 3, tweets and Negative: 2, tweets.

The dataset contains over unique tweets. It was accumulated to analyze corporate responses in relation to the BLM movement. He was a widely known Argentine professional footballer and manager who died on November 25, He was regarded as one of the greatest players in the history of the sport.

The tweets were accumulated between December 10 and December 19, The dataset consists of The hashtag RGB was actually created to celebrate her life. It contains , tweets related to the stock market in English. It also offers a cleaned version of the dataset that comprises 85, unique tweets. The dataset was accumulated to study the impact of public opinions and social events on the stock market.

Utilizing the free PowerPivot Excel Add-in users can perform their own analysis such as who are the top Tweeters, what hashtags are they using and do they have a positive or negative tweet tone. Sample code, used to create this application, is included as a sample and how-to. Details Version:. File Name:. Date Published:. File Size:. System Requirements Supported Operating System. Enter a maximum of 5 comma delimited search queries in the search pane located at the top of the "Topics", "People", "Tone" or "Details" worksheets.

See the Twitter Search Syntax section for more information on the search syntax. You only need to enter your search term once to populate all the worksheets. For your convenience, the search pane is located at the top of each sheet. Click the search icon to retrieve Twitter search queries. Wait for the "Twitter Search Complete" message box. Click OK. Wait for the "Next Steps" message box.