{"title":"An Intelligent and Social-Oriented Sentiment Analytical Model for Stock Market Prediction using Machine Learning and Big Data Analysis","authors":"Muqing Bai, Yu Sun","doi":"10.5121/csit.2022.121819","DOIUrl":null,"url":null,"abstract":"In an era of machine learning, many fields outside of computer science have implemented machine learning as a tool [5]. In the financial world, a variety of machine learning models are used to predict the future prices of a stock in order to optimize profit. This paper preposes a stock prediction algorithm that focuses on the correlation between the price of a stock and its public sentiments shown on social media [6].We trained different machine learning algorithms to find the best model at predicting stock prices given its sentiment. And for the public to access this model, a web-based server and a mobile application is created. We used Thunkable, a powerful no code platform, to produce our mobile application [7]. It allows anyone to check the predictions of stocks, helping people with their investment decisions.","PeriodicalId":91205,"journal":{"name":"Artificial intelligence and applications (Commerce, Calif.)","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial intelligence and applications (Commerce, Calif.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2022.121819","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In an era of machine learning, many fields outside of computer science have implemented machine learning as a tool [5]. In the financial world, a variety of machine learning models are used to predict the future prices of a stock in order to optimize profit. This paper preposes a stock prediction algorithm that focuses on the correlation between the price of a stock and its public sentiments shown on social media [6].We trained different machine learning algorithms to find the best model at predicting stock prices given its sentiment. And for the public to access this model, a web-based server and a mobile application is created. We used Thunkable, a powerful no code platform, to produce our mobile application [7]. It allows anyone to check the predictions of stocks, helping people with their investment decisions.