Social Networks at the Service of Social Innovation and Social Entrepreneurship (The Case Study of Twitter)

Nowadays, many users share their ideas and opinions with others on various social networks. The mass volume of raw data generated on social networks has made them a repository full of ideas, thoughts and concerns of countless users noticing which can play a decisive role in micro and macro decisions. Therefore, the present study seeks to identify people's social concerns by using text analysis methods on Twitter to be included in future plans for social innovation and social entrepreneurship. To achieve this goal, tweets related to social innovation and social entrepreneurship were extracted from Twitter in a new way and analyzed using text mining techniques and algorithms such as topic modeling of LDA and sentiment analysis. The text mining findings showed that users in the field of social entrepreneurship generally focused on issues such as the need to pay attention to employment in Chabahar, holding free events to identify ideas, and opportunities and the problems of raising capital in entrepreneurial projects. Also, in the field of social innovation, users have paid more attention to issues such as the need to care for the disabled, construction of dental centers, the establishment of greenhouses in the southern regions of the country, and empowerment of women. In addition, the analysis of Persian tweets' sentiments about social entrepreneurship and social innovation showed positive results. Given the positive results of analyzing people's feelings towards social entrepreneurship and social innovation and the identified topics, programs and decisions can be considered in future planning to address people's concerns, which can ultimately increase people's satisfaction and their level of well-being.