There are numbers of tools available to mine or scrape data from Twitter. There can be various reasons to mine twitter data such as for your project, marketing and others. But collecting the required data in a structured format can be effective, which can be done with the help of Twitter Scraping Software.

Tools for Collecting Twitter Data:

Here follows some Twitter Data Scraping Software to mine Twitter data:

Beautiful Soup is one of the tools used scraping web pages. It features extensive documentation and community support.
Twitter API: This is a Python wrapper used for performing API requests like searching users, downloading tweets and much more. This library can handle API queries, OAuth and other activities in simple Python interface. However, you should create Twitter app to get OAuths keys and access Twitter’s API
MongoDB: This is an open source document storage database. This features go-to NoSQL database. It makes you to feel like working with JavaScript
PyMongo: This is another effective Twitter Scraper. This is the python wrapper used for interfacing with MongoDB instance. This will allow to connect Python scripts with database and insert or read records
Cronjobs: This is the time based scheduler, which is used to run scripts at set time or intervals.

On successfully storing database on tweets, you can now manipulate data according to your need.

The Twitter Followers Scraper will be enough to scrape twitter messages with keyword or other specifications. You can scrape data within any specified dates, however, the twitter website uses infinite scroll, which will show 20 tweets at a time. But it may keep loading more tweets as you scroll.

Selenium is one of the common and effective solutions to scrape data from twitter with infinite scroll. Selenium can open the web-browser and scroll down to bottom of web page to enable you to scrape. In recent days the tweets also contain images and videos. Perhaps, loading them in the web-browser may be slow. Therefore, if you are planning to scrape thousands of tweets, then it may consume a lot of time and involves intensive processes.

Accessing Twitter with API:

Tweepy, an open-source twitter API wrapper makes the job easy to access Twitter. By using any programming language apart from Python, then you can consider Twitter API documentation.

Besides the above said ways to mine data from twitter, you can also use other effective approaches like:

Streaming API
Search API

The Search API can mine for tweets posted in the past, whereas Streaming will be quick and captures tweets as they are actually posted.

The Search API can sent 180 requests in 15 min timeframe and gets you maximum 100 tweets per Request. However, you can increase this count is by authenticating tweets as an application instead of user. This can increase rate limit to 450 Requests and reduce the time consumed.

The Streaming API can help to collect tweets containing keywords, which will be up to 1% of the total tweets that are currently posted on twitter. Therefore, if the keyword is common or very general and if over 1% of the tweets contain this term, then you may not get the tweets with this term.

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