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Application to Find Like-Minded Twitter Users Austin herrera

Overview Background Related Works Methodology Review Questions and Comments

Background

Friend Recommendation There are many complex algorithms already. Collaborative Filtering Past Behaviors and preferences Content-based Filtering Characteristics of people you like Why mine?

Why Like-Minded Users? Who should be using this? Create a support group Questions Advice Meaningful Conversations Enthusiasm “To give everyone the power to create a support system using social media as a tool.”

Emma Lindström “This is my artwork. Although, I would not call it work. This is what I want to do, what I have to do in life.”

Related Works

Create an account Customize a Profile Set policies Bio Location Preferred categories Connect to other social Media pages Set policies Who can follow you Which users will find you

How does Twellow work? They categorize users Data entered on their Twitter Bio Analysis of Tweets and keywords Twellow Profile Details

TweetStork Tool that finds users who want to… Three Search Techniques Read Share Three Search Techniques Find Related Users Find List Owners Find Re-Tweeters Unfollow Users

How does TweetStork Find Related Users? They find a popular person within your search. Look Through that user’s followers list Filters the followers based on the your preferences

Find List Owners Finds popular accounts similar to yours Finds if they under lists of other users Shows you those users

Find Retweeters Finds popular users that are similar to you Looks at people who retweets them Shows you those users

Unfollow Users TweetStock looks through the your 'following' list It lists the users who aren't following you back and allows you to unfollow them.

Methodology

Methodology Likes and Retweets Key Word Analysis – Tweets Key Word Analysis - Bios Find out who Favorites and Retweets the same things as you. Look through people’s Tweets Look through people’s Profile Bios

Likes and Retweets Take User’s liked tweets Take User’s retweeted tweets Add more weight to retweeted tweets, because on average most tweets are favorited 5x more than retweeted. Issues “Tom” who likes and retweets everything he sees New Users

Finding Keywords Go through tweets over the last year Create a Matrix with the words Column Word Row is Tweet Message Normalize values within Matrix Divide number of keywords by total words

Normalization X ij is the occurrence of the word j in the user’s tweet i. We normalize the value in order to normalize the matrix I create

Review

Background. Why. Who Related Works. Twellow. TweetStork Methodology Background Why Who Related Works Twellow TweetStork Methodology Favorites and RTs Keywords

Questions or Comments Are you guys aware of what problem I want to solve, and why it is important? Do you understand how I plan to solve the problem? How can I better improve my results better than others? Can you offer me tips or ideas for the application?

References Bushell, Annie. Creating Your Successful Future. 2010, eBookwholesaler.  Soufiene Jaffali, Salma Jamoussi, Abdelmajid Ben Hamadou. “Clustering and Classification of Like-Minded People from Their Tweets”, University of Sfax, Tunisia Twellow Website. https://twellow.com/splash/ TweetStork Website. http://www.tweetstork.com/