The question is: how has the system responded to the rigid rules and controls that have been imposed from the top? Did it improve the system, or did it produce gaming and compliance roleplaying? Have system leaders just blindly gone along with this whole "blame culture" that has been nurtured by Queen's Park to deflect blame from the inner circle of connected operators? Are there any leaders wh...

Expertise of annotators has a major role in crowdsourcing based opinion aggregation models. In such frameworks, accuracy and biasness of annotators are occasionally taken as important features and based on them priority of the annotators are assigned. But instead of relying on a single feature, multiple features can be considered and separate rankings can be produced to judge the annotators pro...

Collecting human judgments for music similarity evaluation has always been a difficult and time consuming task. This paper explores the viability of Amazon Mechanical Turk (MTurk) for collecting human judgments for audio music similarity evaluation tasks. We compared the similarity judgments collected from Evalutron6000 (E6K) and MTurk using the Music Information Retrieval Evaluation eXchange 2...

Computerized generation of humor is a notoriously difficult AI problem. We develop an algorithm called Libitum that helps humans generate humor in a Mad Lib R ©, which is a popular fill-in-the-blank game. The algorithm is based on a machine learned classifier that determines whether a potential fill-in word is funny in the context of the Mad Lib story. We use Amazon Mechanical Turk to create gr...

Repetition has been shown to increase subjective truth ratings of trivia statements. This truth effect can be measured in two ways: (a) as the increase in subjective truth from the first to the second encounter (within-items criterion) and (b) as the difference in truth ratings between repeated and other new statements (between-items criterion). Qualitative differences are assumed between the p...