A study on social media opinion about women investors

Abstract

Purpose – to investigate opinions on social networks about women’s investment and its determinants. Social network sentiment research aims to find out why investing remains a very masculine area of life. Research methodology – Twitter social network analysis tools will be used for data mining. Word clouds and sentiment index will be obtained using neural network classification algorithm based on Long Short-Term Memory (LSTM). Findings – the paper obtained the dynamics of three-week opinions on the social network Twitter, considering the main factors that influence women’s choice to invest. Research limitations – only the main factors were investigated and only based on a survey of other authors. Data were extracted from the social network for a limited time. Practical implications – traditionally, investing has remained an area dominated by men. However, women are becoming increasingly financially independent and increasingly involved in the investment process. Therefore, it is very important to analyze the factors that hinder the achievement of investment results. Originality/Value – there are many scientific papers that examine the factors that determine women’s investment choices. However, opinions and sentiments on social networks have not been explored.