A Sentiment Analysis Model For The Strategic Financial Management Challenges In Startups

Abstract

Basically, in startup business the financial and economic news is continuously monitored by the participants of financial market. The future stock prices are determined by absorbing the hypothesis of market based on past information which is reflected from the stock prices. Hence in this paper a sentiment analysis model for the strategic financial management challenges for startups is implemented. First entity input will be given. This entity input is categorized into N data sets. After that strategic financial management planning will be done using entity data. This planning will be researched on different data sets, if it matches then data will be encoded and if it does not match then again data will be moved to the strategic financial management planning block. The encoded data will divide the features into sentimental and entity key features. After that financial controlling will be done. Execution is performed to the data which is controlled by the strategic financial management system. At last performance is evaluated based on the parameters of accuracy, precision, recall, specificity, F1 score, errors and computational time. Hence the results show improved efficiency in sentiment analysis for startups.