Negar Arabzadehghayhazi 2019 Ryerson 3MT® Presentation

Negar Arabzadehghayhazi 2019 Ryerson 3MT® Presentation


Every day, we are bombarded with lots of
online recommendations and advertisements, but how many of us pay
close attention to unwanted information? In terms of online advertising, it’s
interesting that the click rate for display ad campaigns is only 0.1%. This means only one in a thousand ads is clicked. Last year, I wanted to go to a
conference in Italy and I spent many hours planning my trip, checking online
to book the hotel flights, and so on. After I got back, I kept receiving ads
everyday, everywhere. Toronto to Rome, for only 499 bucks.
Hotels in downtown Rome for $30 per night. And I was like, “What’s wrong with
this?” I just got back, I don’t want to go
to Italy every weekend.” I kept receiving
these promotions until I finally unsubscribed all those websites that
frustrated me by sending the same trip offer. So, why do these online recommender
systems not work properly? It’s because, with the existing systems they define me as a victim of my past. With the current systems, every single thing that I do online haunts me for a long time. Even if I’m not interested anymore. But, what if we can make recommendations to users based on what they are going to
be interested in, and not based on what they were interested in? What if we could predict users’ future interests? To know users better, I use social media. More specifically, Twitter. My experiment shows that every user on
social media is influenced by other users. I designed a model that discovers these influential relationships among users, and then I analyzed the previous
tweets of the users and their influencers to predict the user’s future interests. Yes, I can predict what you’re going to
tweet about, even the next day. Let’s face it. We have always been bombarded with ads,
even before the digital era. If advertising is not going away, why
don’t we make it more relevant to you? This is exactly what I am trying to do. Thank you, everyone.

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