Analyzing the growing factor of Financial Markets Using Sentimental Analysis Algorithms
Analyzing the growing factor of Financial Markets Using Sentimental Analysis Algorithms
复制标题
使用情感分析算法分析金融市场的增长因素
DOI：
10.1109/aicera/icis59538.2023.10420179
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Pramod Vishwakarma
中科院分区：
文献类型：
--
作者：
Praveen Kantha;Nallusamy Thiyagarajan;Vikrant Sharma;J. Logeshwaran;Pramod Vishwakarma
情绪分析算法在经济市场中越来越出名。这些算法处理消费者产生的事实，通过情绪预期市场走势，包括恐惧、喜悦、好奇、愤怒和信念。通过解读公众情绪，交易员可以培养更高的金融可能性专业知识。经济增长推动了对雄心壮志的探索，目的是利用情绪分析算法确定推动金融市场增长的因素。我们进行了一项实证评估来观察这种关系。为了验证我们的结果，我们将监督下获得的算法知识和辅助向量机、随机森林和Logistic回归应用到由情绪排名、文本内容和财务指标组成的数据集。我们的研究结果表明，情绪评估与金融、金融服务和市场生产率的表现之间存在着很强的相关性。我们的结论是，情绪分析有可能提供及时和正确的市场洞察力，使投资者能够做出更优秀、更有见识的选择。
Sentiment analysis algorithms have grown to be increasingly famous within the economic markets. Those algorithms process consumer-generated facts to expect market moves through sentiments, including fear, joy, wonder, anger, and belief. By deciphering the public sentiment, traders can cultivate a higher expertise in financial possibilities. Economic growth drives the exploration of ambitions to identify the factors contributing to the growth of financial markets using sentiment analysis algorithms. We administrate an empirical evaluation to observe this relation. To validate our outcomes, we apply supervised gaining knowledge of algorithms and aid Vector Machines, Random Forests, and Logistic Regression to a dataset consisting of sentiment rankings, textual content, and financial indicators. Our findings reveal a robust correlation between sentiment evaluation and the performance of Finance, Financial Services, and Productivity in the marketplace. We conclude that sentiment analysis has the potential to provide well-timed and correct insights into the marketplace, allowing investors to make more excellent, knowledgeable selections.