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Big data analytics in electronic markets
2017
Electronic Markets
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This study not only highlights the role played by sentiment dispersion of investors on the stock market but also carries significant managerial implications for the use of social media as a strategic tool ...
The first paper, titled BElectronic Mobility Market Platforms -A Review of the Current State and Applications of Business Analytics^, by Christoph Willing, Tobias Brandt, and Dirk Neumann, focus the application ...
doi:10.1007/s12525-017-0261-6
fatcat:smgrfdh2jfeolfqddvcibpsiem
Stock Trend Prediction Algorithm Based on Deep Recurrent Neural Network
2021
Wireless Communications and Mobile Computing
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Experiments show that the classification effect is better using this model, and the investor sentiment is obtained more accurately, and the accuracy rate can reach 85%, which lays the foundation for the ...
establishment of the whole stock trend prediction model. ...
In summary, many applications have been made by many scholars using neural network models for stock prediction analysis. ...
doi:10.1155/2021/5694975
fatcat:fnseqjrt6bacfg6ej4frxe6eka
Sentiment Analysis of Twitter Data within Big Data Distributed Environment for Stock Prediction
2015
Proceedings of the 2015 Federated Conference on Computer Science and Information Systems
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This paper covers design, implementation and evaluation of a system that may be used to predict future stock prices basing on analysis of data from social media services. ...
Data was collected during three months and processed for further analysis. ...
Therefore Twitter was chosen for experimental data source for this work on predicting stock market.
II. PREDICTING FUTURE STOCK PRICES
A. ...
doi:10.15439/2015f230
dblp:conf/fedcsis/SkuzaR15
fatcat:hbiswlnkhjcgfnxybvtcvo4yhm
Stock Prediction using ARMA
2018
Zenodo
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The goal is to buy the stock, hold it for a time, and then sell the stock for more than you paid for it. In the stock market, prices rise and fall every day. ...
A stock market is an institution where humans and computers buy and sell shares of companies. For many people, that is the first thing that comes to mind for investing. ...
Harsha Saxena for their step by step guidance , as well as Dr. Ramesh Vasappanavara (Principal) for their suggestions, time to time help which helped us achieving goals and overcoming difficulties. ...
doi:10.5281/zenodo.3361197
fatcat:uqlvrcccrzhh7h3freysoqkbxy
Sentiment Analysis for Indian Stock Market Prediction Using Sensex and Nifty
2015
Procedia Computer Science
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In this research work importance of sentiment analysis for stock market indicators such as Sensex and Nifty has been done to predict the price of stock. ...
From the last twenty years, the application of Internet based technologies had brought a significant impact on the Indian stock market. ...
For BSE (Bombay Stock Exchange) companies Sensex and for NSE (National Stock Exchange) companies Nifty is used as an indicator of stock market prediction. ...
doi:10.1016/j.procs.2015.10.043
fatcat:xrodssz23fgb7ieqbjayfwdtgm
Integrated Mobile Application Based on Machine Learning for East Africa Stock Market
2021
Journal of Information Systems Engineering & Management
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This paper is an attempt to develop a mobile app for stock prediction using LSTM model. ...
Izzah (2017) building on the work of Bini (2016) for using data mining techniques (regression and classification) to predict stock market, developed a mobile app for stock prediction using improved multiple ...
Ethics approval and consent to participate: Not applicable. ...
doi:10.21601/jisem/11008
fatcat:74zm4rrotzahpl4vxhbdgtfdfe
Comparative Study of Real Time Machine Learning Models for Stock Prediction through Streaming Data
2020
Journal of universal computer science (Online)
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The first case study is based on stock prediction from the historical data collected from Google finance websites through NodeJs and the second one is based on the sentiment analysis of Twitter collected ...
Streaming data has been a potential source for real-time prediction which deals with continuous ow of data having information from various sources like social networking websites, server logs, mobile phone ...
Acknowledgement This research work was supported by Fund for Improvement of S&T Infrastructure in Universities and Higher Educational Institutions (FIST) Scheme under Department of Science and Technology ...
doi:10.3897/jucs.2020.059
fatcat:o65rn5pytvdkhot5yfm4gvh73a
Performance Evaluation of Machine Learning Classifiers for Stock Market Prediction in Big Data Environment
2019
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES
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This paper proposed a hybrid stock prediction model based on the collection of qualitative and quantitative data of particular stocks. ...
Historical Prices will be integrated with sentiment values generated from tweets, news and product reviews data to construct the amalgam model using Apache Spark and HDFS for storage of large data. ...
Sentiment Analysis:-Sentiment analysis has been carried out for tweets, news and product reviews data [VII] . ...
doi:10.26782/jmcms.2019.10.00022
fatcat:zbrkbkwf7bcjnbcw5jae2qpeea
Social Sentiment and Stock Trading via Mobile Phones
2016
Americas Conference on Information Systems
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This allows us to offer a new interpretation of how mobile channel stock trading works, and open a new portal for analytics with digital data related to the trading behavior of different investors. ...
In addition, stock trading in the traditional channel probably influences sentiment formation in the market overall. ...
They depict the effects of social sentiment on StockTradingVolume for individual stocks, when they are not explained by the average market return in a given stock market. ...
dblp:conf/amcis/KimLK16
fatcat:lzfn7nryqbblzcyfudacweynxm
The Implication of Tweet's Distribution by Quantizing Stock Values for Inference in the Indian Financial Market: A Sentiment Analysis Approach
2015
International Journal of Computer Applications
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This has proved to be a one of the best method for predicting the sentiment of company present public's mind as a result this sentiment is significant for traders who are interested to invest in that company ...
sentiment analysis and its future prediction.In this paper, we have proposed a promising approach with the help of twitter's API by collecting the tweets on a daily basis and analyzing them for calculating ...
Hence the novel approach is introduced for analysis of target oriented sentiment analysis.
Algorithm: Stock Market Prediction Using Event-Based Supervised Sentiment Learning. ...
doi:10.5120/19207-0903
fatcat:eepwtmwonfb5ddnagekdgae53q
Data science in economics: comprehensive review of advanced machine learning and deep learning methods
2020
Zenodo
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Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. ...
Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. ...
CNN algorithm is also used for analyzing social media data for sentiment analysis [58] . ...
doi:10.5281/zenodo.4087812
fatcat:4flgeabkxvgjrpbydfby3v6tua
Predicting Product Performance with Social Media
2011
Informatică economică
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how social media can be used for predicting the success of a product or service. ...
Social media in general and social networks in particular have turned into marketing tools for organizations and a place where people can express their opinions and attitudes about products.The paper shows ...
Acknowledgement This work was co financed from the European Social Fund through Sectoral Operational Programme Human Resources Development 2007-2013, project number POS-DRU/107/1.5/S/77213 "Ph.D. for a ...
doaj:9de4a33032c949cca60daa0fc27c6443
fatcat:vg3gjwvnvffolersoianwe27ci
Sentiment Predictability for Stocks
[article]
2018
arXiv
pre-print
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In this work, we present our findings and experiments for stock-market prediction using various textual sentiment analysis tools, such as mood analysis and event extraction, as well as prediction models ...
ACKNOWLEDGMENT We thank Francois Belletti for suggesting various links and resources, and Wilson Cai for suggesting the project. ...
Current advancements in sentiment analysis for stock markets focus on prediction for entire indexes. ...
arXiv:1712.05785v2
fatcat:pmvtojn5mjb27nlq64qolvxyly
Sentiment analysis of financial news using unsupervised approach
2020
Procedia Computer Science
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Sentiment analysis aims to determine the sentiment strength from a textual source for good decision making. This work focuses on application of sentiment analysis in financial news. ...
Abstract Sentiment analysis aims to determine the sentiment strength from a textual source for good decision making. This work focuses on application of sentiment analysis in financial news. ...
[8] gave a stock market prediction model based on SentiwordNet (SWN) to give scores of the sentiment indicators and finally derive the overall news sentiment. Hagenau et al. ...
doi:10.1016/j.procs.2020.03.325
fatcat:b3seqfuqkndcfcog73suwdavpy
FinAID, A Financial Advisor Application using AI
2020
International journal of recent technology and engineering
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The application uses 'Plaid' API which allows app to send a request to the corresponding bank server and fetch the account details of an individual. ...
The proposed application will help provide every needy individual a very reliable, easy to use, and cost-efficient solution to their problem of having a personal financial advisor. ...
Rajat, Ahuja and et al [11] , elaborates on using opinion by public along with sentiment analysis of stock market to determine the relations between individual moods and stick market. ...
doi:10.35940/ijrte.a2951.059120
fatcat:4txglohkr5fjtcmeiyegab5l2i
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