DiscoverText is a cloud-based textual analytics tool available for purchase. It is designed to collect data from sources such as social media, blogs and a variety of document formats, and generate tag clouds and reports from the resulting corpus.

Twitter Capture and Analysis Toolset (DMI-TCAT) is a free, open source tool for capturing and analyzing tweets. The tool's web interface is currently closed to researchers outside the University of Amsterdam's Media Studies department, however, the source code is available for download and installation via Github.

Netlytic is a free, web-based tool for analyzing and visualizing text and social network data. It enables users to capture data from sources such as social media, blogs or online forums; identify themes and actors; and generate both chain and personal name networks for further analysis and visualization. Users can import datasets from RSS, cloud storage (Google Drive or Dropbox), Twitter, YouTube, Instagram and a plain text file. Results can be exported in formats accessible to other network analysis tools, such as CSV.

TAGS (Twitter Archiving Google Spreadsheet) v5.1 is a tool for automatically pulling Twitter search results into a Google spreadsheet for further analysis. Users can set TAGS 5.1 to update the resulting archive hourly or at a frequency of their specification, and includes options for filtering out spam, result pagination, and setting an upper limit on tweets collected (to a maximum of 18000).

twXplorer is a free, web-based tool for querying Twitter and exploring the search results based on common words, hashtags and commonly shared links. Each search brings up the 500 most recent tweets for that search term, and the tool permits users to save 'snapshots' for later analysis. twXplorer requires users to log in with their Twitter account.

NodeXL is a free, open source tool for generating and exploring network graphs from Microsoft Excel files. It is particularly suited to data from social media sources, and includes the ability to directly import data from Twitter, YouTube, Flickr and email, with additional plugins available for gathering data from Facebook, Microsoft Exchange, wikis and URLs. The tool generates visualizations that can be adjusted, zoomed and filtered, with additional features for vertex grouping, graphing metric calculations, and automating tasks. NodeXL can both import and export data in GraphML, Pajek, UCINet and matrix formats.

Umigon is a tool used for the sentiment analysis of texts. It is one of the tools of the Nocode app which is a suite of text analysis tools. Results can be exported in Excel or CSV format for further analysis.

It was formerly a stand alone web-based and open-source tool for the sentiment analysis of tweets. From a person's Twitter handle, Umigon retrieved that account's tweets and processed them for sentiment while accounting for factual statements (ex: "I hate war" will be classified has negative, and "war in Syria" will be classified as neutral). Tweets could also be pasted manually in the entry box provided. Beyond sentiment analysis, Umigon could identify characteristics such as whether the tweet contains a question, whether it contains possible promotional/commercial subject matter, or temporal indicators based on tense.

The developer of this application can be reached on Twitter.

Sifter provides search and retrieve access to every undeleted Tweet in the history of Twitter. Users can submit three historical Twitter estimate requests per day using a variety of Gnip PowerTrack rules. When the query is done, Sifter generates an email estimating the approximate number of tweets responsive to the query and the cost to get access to the data via DiscoverText. Once the data is licensed by Texifter, we store the Tweets in a free trial Enterprise DiscoverText account where you can perform advanced text analytics to search, filter, cluster, code, and machine classify the data.

STACK is an extensible social media research toolkit designed to collect, process, and store data from online social networks. The toolkit is an ongoing project via the Syracuse University iSchool, and currently supports the Twitter Streaming API. Collecting from Facebook public pages and Twitter search API are under development. The toolkit architecture is modular and supports extending. Basic Linux / Mac command line skills needed.

To learn more: https://github.com/bitslabsyr/stack

140kit provides a management layer for tweet collection and analysis.

Raw data cannot be passed through to the users, but any analytical process can be run across your dataset, and the data is held for as long as the user wants. When new analytical processes are created, they can be run on existing sets of data. 140kit does not claim any control of the analysis, however it retains ownership of the data collected.

Current limits:

User: 20,000 Tweets per Dataset or until Dataset time elapses

Academic User: 500,000 Tweets per Dataset or until Dataset time elapses