posted by Lexing Xie

We look for new team members who value curiosity, critical thinking, and diversity in ideas, skills, and cultural perspectives.

posted by Marian-Andrei Rizoiu , edited by Lexing Xie

“The fundamental scarcity in the modern world is the scarcity of attention.” – Herbert A. Simon.

Human attention is a limited resource and influencing the mechanisms governing its allocation is the holy grail of advertisement. Our ICWSM’17 paper applies the recent HIP popularity modeling to further examine popularity under promotion and answer questions such as:

• How much promotion is required for this item to rise to the top 5% in popularity?
• How fast will an item respond to a given amount of promotion?
• Why is constant promotion desirable?

posted by Marian-Andrei Rizoiu , edited by Lexing Xie

One major gap in understanding social media is to precisely quantify the relationship between the popularity of an online item and the external promotions it receives. Our recent WWW’17 paper supplies the missing link. We use a mathematical model to describe the continuous interaction between external promotions (e.g. tweets about a video) and popularity dynamics (e.g. daily views). This in turn answers several practical questions:

• Can we explain the complex multi-phased popularity dynamics widely seen online?
• Can one predict what could become viral?
• Can one predict what would not become viral even if heavily promoted?

posted by Siqi Wu, edited by Marian-Andrei Rizoiu and Lexing Xie

We are in an era when information consumption and production are democratized. Regular users not only consume information, but they digest, mutate and produce new information which gets passed on to other users. Prompted by a press inquiry from the Polish online news www.press.pl, we analyze the impact of these emergent sources of information versus traditional media, in the context of politics. More precisely, we study how YouTube videos posted by two traditional news sources (BBC news/UK, ABC news/USA) and two emergent online news sources (The Alex Jones Channel, The Young Turks) are viewed around the time of the US political elections of 2016.

posted by Lexing Xie

This post is the first of a series on modeling social media popularity using the Hawkes Intensity Process. “Expecting to be HIP (II)” gives an overview of results and interpretations on a large YouTube video dataset. “Expecting to be HIP (III)” further quantifies the effects and interpretations of promotion.

posted by Lexing Xie

Markov chains and random walk on graphs are long-standing subjects in applied math and related disciplines. Given a markov chain / transition matrix / graph, properties of the random walk such as steady state distribution, mixing time are well-studied. Only in recent years, however, the inverse problem has started gaining interest – that is, given some measurements after random walk on a graph, infer some version of the graph. This blog post compares three related but different problem settings in recent literature from (Kumar15), (Mackay15) and (Xie13).

posted by Siqi Wu, with edits from Lexing Xie

Australia has great weather for the ourdoors, no matter it’s winter or summer – that’s what we did, and here’s photo proof.

posted by Minjeong Shin and Lexing Xie

Our work received some pulicity in the “fall” conference season internationally and in Australia.

posted by Swapnil Mishra

Predicting popularity as number of retweets a tweet will get is an important and difficult task. It’s unclear which approaches, settings and features works best. Our current CIKM ‘16 paper bridges this gap by comparing across feature driven and point process approaches under both regression and classification settings.

posted by Dawei Chen

The problem of recommending tours to travellers is an important and broadly studied area. We consider the task of recommending a sequence of points-of-interest (POI), that simultaneously uses information about POIs and routes.

posted by Dongwoo Kim

Relational knowledge graphs formalise our understanding about the world and help us reason and infer in a wide range of tasks. The construction of a knowledge graph is an active research area with many important and challenging research questions. Throughout this research, we address some important problems in the knowledge graph construction and propose novel statistical relational models to solve the problems.