In this paper, we investigate how conventional and unconventional monetary policy shocks affect the stock market of eight advanced economies, namely, Canada, France, Germany, Japan, Italy, Spain, U.K., U.S., conditional on state sentiment. regard, use a panel vector auto-regression (VAR) with monthly data (on output, prices, equity metrics policies, consumer business sentiments) over period Jan...

The effects of real-world events on the dynamics and sentiment expressed through online conversations are not entirely understood. In particular, highly polarized communities, deeply invested in outcome a particular event naturally tend to have contrasting emotional sensitivity exogenous events. this study, we analyze Twitter during Mexico versus Germany group match 2018 FIFA World Cup investig...

This paper investigates how monetary policy shock affects the stock market of United States (US) conditional on states investor sentiment. In this regard, we use a recently developed estimator that uses high-frequency surprises as proxy for structural shocks, which in turn is achieved by integrating current short-term rate surprises, are least affected an information effect, into vector autoreg...

Sentiment lexicon is an important tool for identifying the sentiment polarity of words and texts. How to automatically construct sentiment lexicons has become a research topic in the field of sentiment analysis and opinion mining. Recently there were some attempts to employ representation learning algorithms to construct a sentiment lexicon with sentiment-aware word embedding. However, these me...

Sentiment analysis and opinion mining are actively explored nowadays. One of the most important resources for the sentiment analysis task is sentiment lexicon. This paper presents our study in building domain-specific sentiment lexicon for Indonesian language. Our main contributions are (1) methods to expand sentiment lexicon using sentiment patterns and (2) a technique to classify the polarity...

We perform principal components analyses of the University of Michigan Index of Consumer Sentiment and TV sentiment in order to gain information on their structure and information content. By introducing the new sentiment variable TV sentiment, gathered from sentiment from statements from over 10,000 TV news broadcasts in the United States, we nd that TV sentiment adds great value in nowcasting...

This document provides an overview of the Text Analysis Conference 2013 Knowledge Base Population Sentiment Slot Filling (SSF) track. Sentiment Slot Filling was a new task added this year, and pushed the state of the art in sentiment by requiring teams to provide sentiment analysis in open domains across a variety of genres. The task focused on identifying the polarity of sentiment as well as s...

Lyric-based song sentiment classification seeks to assign songs appropriate sentiment labels such as light-hearted and heavy-hearted. Four problems render vector space model (VSM)-based text classification approach ineffective: 1) Many words within song lyrics actually contribute little to sentiment; 2) Nouns and verbs used to express sentiment are ambiguous; 3) Negations and modifiers around t...