With over 320 million monthly active users, Twitter continues to be a rich and vast resource for data on the Web. All that’s left to do is identify the opportunities it presents to your business and capitalize on them. Here are the top uses of twitter data.

2. Twitter is a goldmine of information, and
the fact that every tweet posted is
publicly accessible makes it an ideal
web data source.

3. There are two ways to extract data from Twitter:
• Hitting their API
• Web Scraping

4. Twitter’s API provides a straightforward
way to query and fetch data in JSON
format.

5. Web Scraping is used in cases where
the limitations of API are slowing down
the extraction.

6. Twitter has a user-base that covers people from
all industries and spans across geographies. This
makes Twitter data useful for businesses looking
to stay up-to date with the changing trends in
their respective markets.

7. ❖ Brand monitoring
❖ Competitor tracking
❖ Sentiment analysis
❖ Training machine learning models
❖ Industry trends analysis

8. Brand monitoring is the best way to observe what people
are saying about your business on the Internet.

9. Since your consumers are likely to voice their opinions
about your brand and product on twitter, extracting
Twitter data will help you listen to them better.

10. Competitor monitoring has become an essential business
intelligence task as it helps companies know what their
competitors are up to and come up with counter
strategies.

11. Since every business entity is active on Twitter these
days, you can easily track any number of competitors by
setting up a web crawling system to crawl and extract
relevant data from the social media platform.

12. Sentiment analysis is essentially the process of identifying
the emotional tone from a series of words, used to gain
an understanding of the opinions, emotions and attitudes
expressed via an online mention.

13. Twitter is a platform where users express their views about
brands, products or notable world events. Sentiment
analysis can be performed on large datasets of tweets to
identify the public opinion on various things.

14. Provided with the training data, machine systems can
learn to do correlational tasks like classification,
clustering, attribution etc. User generated data can also
be used for building content corpus, which helps
machines understand human languages on a deeper
level.

15. Since Twitter has an abundance of user generated
content in the form of tweets, it makes for an ideal source
of data for machine learning training.

16. Staying ahead of the competition requires foresight into
the future of your industry. This has become all the more
important in this fast-paced business world.

17. Being one of the most popular social media platforms out
there, Twitter reflects all the current events and trending
information that’s relevant for businesses.

18. We created datasets by downloading 5,000 tweets
(excluding retweets) for each of ‘iPhoneX’ and ‘iPhone8’
hashtag.
Let’s look at some data visualizations that we created using
them.

22. With over 320 million monthly active users, Twitter
continues to be a rich and vast resource for data on the
Web. All that’s left to do is identify the opportunities it
presents to your business and capitalize on them.

23. Got Questions? Connect with us at
www.promptcloud.com
sales@promptcloud.com