Guha, Satarupa (International Institute of Information Technology, Hyderabad) | Chakraborty, Tanmoy (University of Maryland, College Park) | Datta, Samik (Flipkart Internet Pvt. Ltd.) | Kumar, Mohit (Flipkart Internet Pvt. Ltd.) | Varma, Vasudeva (International Institute of Information Technology, Hyderabad)
An overwhelming amount of data is generated everyday onsocial media, encompassing a wide spectrum of topics. With almost every business decision depending on customer opinion, mining of social media data needs to be quick and easy.For a data analyst to keep up with the agility and the scale of the data, it is impossible to bank on fully supervised techniques to mine topics and their associated sentiments from social media. Motivated by this, we propose a weakly supervised approach (named, TweetGrep) that lets the data analyst easily define a topic by few keywords and adapt a generic sentiment classifier to the topic – by jointly modeling topics and sentiments using label regularization. Experiments with diverse datasets show that TweetGrep beats the state-of-the-art models for both the tasks of retrieving topical tweet sand analyzing the sentiment of the tweets (average improvement of 4.97% and 6.91% respectively in terms of area under the curve). Further, we show that TweetGrep can also be adopted in a novel task of hashtag disambiguation, which significantly outperforms the baseline methods.
Microblogging services such as Twitter offer great opportunities for analyzing the reactions of a wide audience with respect to current events. In this paper, we explore the correlation between types of user engagement and events centered around celebrities (e.g., personal or professional events involving Actors, Musicians, Politicians, Athletes).
With the advent of Amazon's Alexa and Siri's consistent capacity to take on more chores (and get more and more sassy), many are wondering: what's next for natural language understanding and conversational voice interfaces? There are several companies neck-and-neck in this race. There's Wit.ai, the company Facebook acquired -- you can toy around with demo. Apple has its HomeKit and, with it, is doing what Apple does best -- kicking ass. One company hot on the trail of natural language understanding is MindMeld.
The biggest hardware and software arrival since the iPad in 2010 has been Amazon's Echo voice-controlled intelligent speaker, powered by its Alexa software assistant. But just because you're not seeing amazing new consumer tech products on Amazon, in the app stores, or at the Apple Store or Best Buy, that doesn't mean the tech revolution is stuck or stopped. They are: Artificial intelligence / machine learning, augmented reality, virtual reality, robotics and drones, smart homes, self-driving cars, and digital health / wearables. Google has changed its entire corporate mission to be "AI first" and, with Google Home and Google Assistant, to perform tasks via voice commands and eventually hold real, unstructured conversations.