Related papers: An Exploration of Cursor tracking Data
An increasing need to analyse event-centric cross-lingual information calls for innovative user interaction models that assist users in crossing the language barrier. However, datasets that reflect user interaction traces in cross-lingual…
With an expansive and ubiquitously available gold mine of educational data, Massive Open Online courses (MOOCs) have become the an important foci of learning analytics research. The hope is that this new surge of development will bring the…
A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how…
We examine the properties of all HTTP requests generated by a thousand undergraduates over a span of two months. Preserving user identity in the data set allows us to discover novel properties of Web traffic that directly affect models of…
In competitive search settings such as the Web, many documents' authors (publishers) opt to have their documents highly ranked for some queries. To this end, they modify the documents - specifically, their content - in response to induced…
Users' detailed browsing activity - such as what sites they are spending time on and for how long, and what tabs they have open and which one is focused at any given time - is useful for a number of research and practical applications.…
Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper,…
Predicting users' preferences based on their sequential behaviors in history is challenging and crucial for modern recommender systems. Most existing sequential recommendation algorithms focus on transitional structure among the sequential…
The cumulative effect of collective online participation has an important and adverse impact on individual privacy. As an online system evolves over time, new digital traces of individual behavior may uncover previously hidden statistical…
In online platforms, the impact of a treatment on an observed outcome may change over time as 1) users learn about the intervention, and 2) the system personalization, such as individualized recommendations, change over time. We introduce a…
Despite the prevalence of sentiment-related content on the Web, there has been limited work on focused crawlers capable of effectively collecting such content. In this study, we evaluated the efficacy of using sentiment-related information…
People use search engines to find answers to questions related to their health, finances, or other socially relevant issues. However, most users are unaware that search results are considerably influenced by search engine marketing (SEM).…
The Web has enabled one of the most visible recent developments in education---the deployment of massive open online courses. With their global reach and often staggering enrollments, MOOCs have the potential to become a major new mechanism…
Political polarization appears to be on the rise, as measured by voting behavior, general affect towards opposing partisans and their parties, and contents posted and consumed online. Research over the years has focused on the role of the…
Session-based recommendation is gaining increasing attention due to its practical value in predicting the intents of anonymous users based on limited behaviors. Emerging efforts incorporate various side information to alleviate inherent…
The digital information landscape has introduced a new dimension to understanding how we collectively react to new information and preserve it at the societal level. This, together with the emergence of platforms such as Wikipedia, has…
Wikipedia is one of the most visited websites in the world and is also a frequent subject of scientific research. However, the analytical possibilities of Wikipedia information have not yet been analyzed considering at the same time both a…
Peer recommendation is a crowdsourcing task that leverages the opinions of many to identify interesting content online, such as news, images, or videos. Peer recommendation applications often use social signals, e.g., the number of prior…
Choice decisions made by users of online applications can suffer from biases due to the users' level of engagement. For instance, low engagement users may make random choices with no concern for the quality of items offered. This biased…
Moving groups are routinely faced with a choice of different routes as part of their daily lives, such as choosing between exits from a building. Differences in moving speeds and environmental constraints often lead to individuals being…