Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy
نویسنده
چکیده
In today’s world, globalisation is not only affecting inter-culturalism but also linking markets across the globe. Given that all markets are affecting each other and are not only driven by fundamental data but also by sentiments, sentiment analysis regarding the markets becomes a tool to predict, anticipate, and milden future economic crises such as the one we faced in 2008. In this paper, an approach to improve sentiment analysis by exploiting relationships among different kinds of sentiment, together with supplementary information, from and across various data sources is proposed.
منابع مشابه
Weibo sentiments and stock return: A time-frequency view
This study provides new insights into the relationships between social media sentiments and the stock market in China. Based on machine learning, we classify microblogs posted on Sina Weibo, a Twitter's variant in China into five detailed sentiments of anger, disgust, fear, joy, and sadness. Using wavelet analysis, we find close positive linkages between sentiments and the stock return, which h...
متن کاملA Grouping Hotel Recommender System Based on Deep Learning and Sentiment Analysis
Recommender systems are important tools for users to identify their preferred items and for businesses to improve their products and services. In recent years, the use of online services for selection and reservation of hotels have witnessed a booming growth. Customer’ reviews have replaced the word of mouth marketing, but searching hotels based on user priorities is more time-consuming. This s...
متن کاملAnalysing the Bilateral Relationship between Technological Readiness and Innovation of Countries by Considering the Mediating Effect of GDP
During the past decade, the World Economic Forum has published its annual reports in which the Global Competitiveness Index is included. This paper aims to investigate the key factors for achieving an innovation-driven economy. In this paper, we used partial canonical correlation analysis (PCCA) to examine the relationships between key pillars in “efficiency enhancers” and “business sophisticat...
متن کاملA Deep Learning Approach towards Cross-Lingual Tweet Tagging
Named Entity Recognition (NER) is important in analysing the context of a statement and also the sentiments associated with it. Although Twitter Data is noisy, it is valuable due to the amount of information it can provide. Therefore, NER for Twitter Data is necessary. Our model aims to extract the named entities from tweets using a Recurrent Neural Network Core. Long Short Term Memory (LSTM) w...
متن کاملMarket Orientation, Social Entrepreneurial Orientation, and Organizational Performance: The Mediating Role of Learning Orientation
One of the emerging research areas in the strategic orientation is how to transfer different orientations from the commercial sector to the non-profit sector. Therefore, the objective of this study is to determine the mediating effect of Learning Orientation on the Market Orientation, Social Entrepreneurial Orientation, and Organizational Performance in the non-profit sector. The data from more...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017