102 citations · 230 across the 11 of their papers we have counts for
11 papers
Klout Topics for Modeling Interests and Expertise of Users Across Social Networks
Sarah Ellinger, Prantik Bhattacharyya, Preeti Bhargava +1
This paper presents Klout Topics, a lightweight ontology to describe social media users' topics of interest and expertise. Klout Topics is designed to: be human-readable and consum…
Analyzing users' sentiment towards popular consumer industries and brands on Twitter
Guoning Hu, Preeti Bhargava, Saul Fuhrmann +2
Social media serves as a unified platform for users to express their thoughts on subjects ranging from their daily lives to their opinion on consumer brands and products. These use…
Lithium NLP: A System for Rich Information Extraction from Noisy User Generated Text on Social Media
Preeti Bhargava, Nemanja Spasojevic, Guoning Hu
In this paper, we describe the Lithium Natural Language Processing (NLP) system - a resource-constrained, high- throughput and language-agnostic system for information extraction f…
Global Entity Ranking Across Multiple Languages
Prantik Bhattacharyya, Nemanja Spasojevic
We present work on building a global long-tailed ranking of entities across multiple languages using Wikipedia and Freebase knowledge bases. We identify multiple features and build…
High-Throughput and Language-Agnostic Entity Disambiguation and Linking on User Generated Data
Preeti Bhargava, Nemanja Spasojevic, Guoning Hu
The Entity Disambiguation and Linking (EDL) task matches entity mentions in text to a unique Knowledge Base (KB) identifier such as a Wikipedia or Freebase id. It plays a critical…
DAWT: Densely Annotated Wikipedia Texts across multiple languages
Nemanja Spasojevic, Preeti Bhargava, Guoning Hu
In this work, we open up the DAWT dataset - Densely Annotated Wikipedia Texts across multiple languages. The annotations include labeled text mentions mapping to entities (represen…
Mining Half a Billion Topical Experts Across Multiple Social Networks
Nemanja Spasojevic, Prantik Bhattacharyya, Adithya Rao
Mining topical experts on social media is a problem that has gained significant attention due to its wide-ranging applications. Here we present the first study that combines data f…
Actionable and Political Text Classification using Word Embeddings and LSTM
Adithya Rao, Nemanja Spasojevic
In this work, we apply word embeddings and neural networks with Long Short-Term Memory (LSTM) to text classification problems, where the classification criteria are decided by the…
Identifying Actionable Messages on Social Media
Nemanja Spasojevic, Adithya Rao
Text actionability detection is the problem of classifying user authored natural language text, according to whether it can be acted upon by a responding agent. In this paper, we p…
Klout Score: Measuring Influence Across Multiple Social Networks
Adithya Rao, Nemanja Spasojevic, Zhisheng Li +1
In this work, we present the Klout Score, an influence scoring system that assigns scores to 750 million users across 9 different social networks on a daily basis. We propose a hie…
When-To-Post on Social Networks
Nemanja Spasojevic, Zhisheng Li, Adithya Rao +1
For many users on social networks, one of the goals when broadcasting content is to reach a large audience. The probability of receiving reactions to a message differs for each use…