This paper has had quite an adventure, and it finally has a home. The WikiTalkEdit dataset/paper tests whether the predictors of emotion change in a two-party conversation, are also predictors of behavioral change. The paper tests different language models and provide linguistic insights about the predictors of each kind of change. Inspired by a conversation... Continue Reading →
This was one of most interesting and challenging datasets I explored. The original dataset was collected by a brilliant team of researchers over at CMU. If you want to see how awesome they are, check out their video describing the data: https://www.youtube.com/watch?v=BVAAhIUtf9U&ab_channel=JordanBoyd-Graber Here's the description provided by Jordan Boyd-Graber: Machine learning techniques to detect deception... Continue Reading →
More details at https://sites.google.com/view/affcon2020/home See you in New York on Feb 7, 2020!!
It has long been known that human affect is context-driven, and that labeled datasets should account for these factors in generating predictive models of affect. This motivates our Shared Task, which is organized in collaboration with researchers at Megagon Labs and is built upon the HappyDB dataset, comprising human accounts of `happy moments'. I'll add... Continue Reading →
The 4th CL-SciSumm 2018 Shared Task, sponsored by Microsoft Research Asia. The Shared Task on the relationship mining and scientific summarization of computational linguistics research papers was organized at SIGIR from 2017-2019. Scientific summarization can play an important role in developing methods to index, represent, retrieve, browse and visualize information in large scholarly databases. More... Continue Reading →
The WKWSCI Sentiment Lexicon by Christopher S. G. Khoo, Sathik Basha Johnkhan and Jin-Cheon Na is based on the 6of12dict lexicon, and currently covers adjectives, adverbs and verbs. The words were manually coded with a value on a 7-point sentiment strength scale. The effectiveness of the four sentiment lexicons for sentiment categorization at the document-level and sentence-level was evaluated using an Amazon product review dataset.... Continue Reading →