Empirical research has shown that incorporating big data into tourism and hospitality
forecasting significantly improves prediction accuracy. This study presents a comprehensive …

This paper applies algorithmic analysis to financial market text-based data to assess how
narratives and sentiment might drive financial system developments. We find changes in …

This paper examines several ways to extract timely economic signals from newspaper text
and shows that such information can materially improve forecasts of macroeconomic …

Despite the important role of the sentiment of customer reviews in the tourist decision-
making process, it has received limited attention from the field of tourism demand …

In this paper, we address the task of zero-shot cross-lingual news sentiment classification.
Given the annotated dataset of positive, neutral, and negative news in Slovene, the aim is to …

This paper shows that newspaper articles contain signals that can materially improve real‐
time nowcasts of real GDP growth for the Euro area. Using articles from 15 popular …

Purpose This study aims to examine whether and when real-time updated online search
engine data such as the daily Baidu Index can be useful for improving the accuracy of …

Can we use newspaper articles to forecast economic activity? Our answer is yes; and, to this
end, we propose a high-frequency Text-based Economic Sentiment Index (TESI) and a Text …

This paper constructs three monthly sentiment indices based on social media, traditional
newspapers, and Internet news. The predictive power of the social media sentiment index …

This article surveys the economic literature on the role of mass media and social media for
the dissemination of news about the economy. Focusing on studies that use media content …