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 be-coming 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.