scholarly journals Twitter Sentiment Analysis: How to Hedge Your Bets in the Stock Markets

Author(s):  
Tushar Rao ◽  
Saket Srivastava
2021 ◽  
Author(s):  
Jheng-Long Wu ◽  
Min-Tzu Huang ◽  
Chi-Sheng Yang ◽  
Kai-Hsuan Liu

2015 ◽  
Vol 5 (2) ◽  
pp. 308
Author(s):  
Radu Nicoara

<p class="ber"><span lang="EN-GB">NewsInn is an A.I. Driven Algorithm that processes and conglomerates news from major news publications. It uses an opinion extraction algorithm to do a sentiment analysis on every news article. </span></p><p class="ber"><span lang="EN-GB">Considering that stock markets are heavily influenced be world news, we conducted a study to show the link between the detected sentiment inside the news, and the most used Stock Market Indexes: S&amp;P 500, Dow Jones and NASDAQ. Results showed an almost 70.00% accuracy in predicting market fluctuation two days in advance.</span></p>


2020 ◽  
Vol 22 (4) ◽  
pp. 338-361
Author(s):  
Xiaomeng Ma ◽  
Dong Zou ◽  
Chuanchao Huang ◽  
Shuliang Lv

2012 ◽  
pp. 4-32
Author(s):  
I. Borisova ◽  
B. Zamaraev ◽  
A. Kiyutsevskaya ◽  
A. Nazarova ◽  
E. Sukhanov

Conditions and features of the Russian economy development in 2011 are considered in the article. Having caused unprecedented outflow of the capital abroad, rising tension and turbulence on the world financial and stock markets have not broken off recovery of the Russian economy. Crisis recession was overcome. Record-breaking low inflation, rapid credit restoration and active government adjustment neutralized negative effects of the external tension and supported economic growth, having encouraged consumer and investment demand.


Author(s):  
Agung Eddy Suryo Saputro ◽  
Khairil Anwar Notodiputro ◽  
Indahwati A

In 2018, Indonesia implemented a Governor's Election which included 17 provinces. For several months before the Election, news and opinions regarding the Governor's Election were often trending topics on Twitter. This study aims to describe the results of sentiment mining and determine the best method for predicting sentiment classes. Sentiment mining is based on Lexicon. While the methods used for sentiment analysis are Naive Bayes and C5.0. The results showed that the percentage of positive sentiment in 17 provinces was greater than the negative and neutral sentiments. In addition, method C5.0 produces a better prediction than Naive Bayes.


Corpora ◽  
2019 ◽  
Vol 14 (3) ◽  
pp. 327-349
Author(s):  
Craig Frayne

This study uses the two largest available American English language corpora, Google Books and the Corpus of Historical American English (coha), to investigate relations between ecology and language. The paper introduces ecolinguistics as a promising theme for corpus research. While some previous ecolinguistic research has used corpus approaches, there is a case to be made for quantitative methods that draw on larger datasets. Building on other corpus studies that have made connections between language use and environmental change, this paper investigates whether linguistic references to other species have changed in the past two centuries and, if so, how. The methodology consists of two main parts: an examination of the frequency of common names of species followed by aspect-level sentiment analysis of concordance lines. Results point to both opportunities and challenges associated with applying corpus methods to ecolinguistc research.


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