­In the era of big data, min/max searching from bulk data arrays is one of the most important and widely used fundamental operations in data-intensive applications such as sorting, ranking, bioinformatics, data mining, graph processing, and route planning. Online news and social media require real-time ranking using fast min/max searching from...

­Node classification in real-world attributed networks is a central analytical task that is a growing research area. In real-world networks, a large portion of node classes only contain limited labeled instances. Many prevailing graph machine learning methods typically rely upon the availability of sufficient labeled data. However, the long-tail...

Background Cyberbullying, defined as “aggressively intentional acts carried out by a group or an individual using electronic forms of contact, repeatedly or over time against victims who cannot easily defend themselves,” has been rising at an alarming rate. Previous research has found that nearly 43% of teens in the United States have been...

Background Social media has become an indispensable tool in the face of natural disasters due to its broad appeal and ability to quickly disseminate information. For instance, Twitter is an important source for disaster responders to search for (1) topics that have been identified as being of particular interest over time, i.e., common topics such as...

BackgroundTextual information is one of the most significant portions of data that users generate by participating in different online activities such as leaving online reviews and posting tweets. On one hand, textual data consists of abundant information about users’ behavior, preferences, and needs which is critical for understanding them. For...

Social media services like Twitter have become a prominent source of research data for both academic and corporate applications because of the large amount of data available. Twitter allows researchers to obtain low-cost data samples, but past research has shown the data is not a random distribution and thus, is unrepresentative of the population. As...

The explosive and viral nature of social media creates massive amounts of high-dimensional data. Features such as hashtags, keywords, or slang words are created every day and quickly become popular within a short period of time. However, social media data is not fully structured and its features are usually not predefined. One way to resolve this problem...

Background Recommendations of user-to-user relationships (“friends”) and items (e.g., products, services) have become integral to the social media experience. When implemented effectively, both the user and the platform gain value. Unlike established sites however, newly launched social media sites lack the historical data typically necessary...

Background The overturning of the Internet Privacy Rules by the Federal Communications Commissions (FCC) in late March 2017 allows Internet Service Providers (ISPs) to collect, share and sell their customers’ web browsing data without their consent. With third-party trackers embedded in webpages, this ruling places privacy under further risk....

Background Tremendous volumes of sequential event data continue to be generated across diverse technological domains. Whether they be “retweets” sprouting across the social media network Twitter, stock trades, or ride-share vehicle usage patterns, effective data processing of past occurrences can improve near-term predictability of future...