Twitance is a recommendation tool that analyzes tweets and Twitter activity to provide recommendations to help users better engage audiences. It checks responses to tweets like retweets, replies, and favorites to determine influencers. This helps brands and individuals focus their strategies and plan their tweets. The tool will provide two recommendation lists - a universal list and a followers list - as well as reach analytics over time and influential users for a given tweet. It is built using Ruby on Rails, MongoDB, Elastic Search, and the Twitter API.

1. TWITANCE
Guided By:
Prof.Geeta Patil
Sponsored By:
Josh Software
Group Members:
Ashish Singh
Rohit Khatana
Jitendra Sharma
Aravind S

2. TWITANCE
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Recommendation Tool
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Twitter analytics
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Checks the response on tweets
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Uses this response to better engage with
the audience

3. TWITANCE
Based On Twitter
Why This?
Whenever we tweet on twitter its always good to
have an idea of the impact that tweet had and also
the activity around that tweet so as to better engage
with interested audience.
Because, people like to know their influence in social
media, which will help them to plan their strategies
in case of brands and help people to focus more on
them.

4. Use -cases
•
Martha tweets about the cooking very
frequently.
• If she has a new recipe for a dish and she
tweets about it.
• She wants to know response(RT,reply,favorite)
on that tweet.

5. • So as to better engage with people who are
more interested in her recipes.
• Doing so its more likely that interested
people may come up with suggestions and
Rts eventually leading to wider reach.

6. Impact of promoter
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●
Very recently chennai express was
released and there was a lot of activities
around the #chennaiexp and @iamsrk.
Now if we plan to tweet about the movie.
Mentioning @iamsrk increases the
possibility of that tweet being retweeted by
@iamsrk. Thus increasing the reach of
your tweet.

7. • Normally people don't know who his
promoter would be, while tweeting related
to a particular topic.
• Twitance will help them get to a decision
regarding this.

8. ANOTHER USE-CASE
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●
Let's suppose someone wants to survey
about the rape-cases in India . And he
tweets about it.
Then on the basis of tweet's impact in India
.We can give him the best person who can
help him out when he comes to India.

9. Similar Apps which we found During over research
TWEET REACH:
• Processes your tweets and looks for audience and
possible reach , mentions the list of contributors
KLOUT:
• Measures the size of your social media network.
TWEET ANALYZER:
• Provides influential score on the basis of popularity

10. TWIST:
• Offers Trends on Twitter on the basis of
keywords and hash tag.
TWITTURLY:
• Keeps track of popular URLs on twitter.
• Works similar to Digg.

11. Milestones
With Twitance our main aim is to finally be able to show a
list of twitter users to the authorized user as
recommendations and analytics of a particular tweet.
Thus based on the analysis, twitter user can get a fair idea
of their reach through tweets.
Our Main idea has these many components:• Two lists of recommendations for a particular tweet:
 Universal List

12.  Followers List
• First a Graph(a pictorial representation) that
will show the reach and chains as shown in
the picture below.
• So the basic idea is all the shares from
Gautam’s tweet will lie in his circle and add to
his contribution in the publicity of this post.

13. TWEET ANALYTICS

14. 2. Reach over time
In this reach over time is shown this means which
users contributed to the post over time and their
influence.Important contributors are highlighted.

15. 3. Influencers and other stats
This shows the list of people that influenced
the post most this required some math.
Gender and Location wise stats will also be
there.

17. Technologies Used:
• Ruby On Rails:
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Open source web application frame
Model view controller design principles
Active Record Pattern
Encourages developers to use restful routes
Availability of numerous gems(libraries) makes your
life easier.

18. • Mongo DB:
 Cross platform document oriented database
system
 No SQL (scheme-less)
 Supports restful operations (CRUD)
 Favors JSON like documents with dynamic
schemas.

19. • Elastic Search [Analyzers + Efficient Searching ]
 Wrapper on Lucene project.
 Open source , distributed server side search
engine.
 Consists various analyzers like Snowball
anaylzer.
 Provides an approximate result if actual result
not found.

20. • Twitter API :
 Provides JSON type API.
 Provides services strictly to the authorized
users.
 Provides all public data related to twitter
users which includes
Followers, Friends, Tweets and public info of
users.
 Search Rate limit : 180/user/15 min window
 User Rate limit : 15/user/15 min window

21. REFERENCES:
•
IEEE PAPER :Credibility in Context: An Analysis of Feature Distributions in Twitter
John O’Donovan, Byungkyu Kang, Greg Meyer, Tobias Hollerer University of
California,Santa Barbara, USA
• www.ruby.org
• www.elasticsearch.org
• www.rubyonrails.in

22. THANK YOU!!
Made By :Rohit Khatana
Aravind S
Jitendra Sharma
Ashish Singh