Big Data in Analysis of Social Media Based on the Example of Twitter

Contemporary organizations in order to meet increasing customer's demands seek new data sources describing their behaviors and preferences. In recent times, Internet and social media became important customers data repositories. Social media contain various information concerning customer's behaviors and their shopping preferences. Simultaneously development of various instruments for Big data processing caused social media to become subject of numerous analyses. The main goal of this paper is to present an idea of Big data analysis. The subject of this analysis is Twitter social network. Frequency of clients posts regarding chosen companies and their products is investigated. Six thousand tweets on Samsung and Apple products are explored. The exploration is conducted with the usage of text mining techniques, and sentimental analysis. It is performed in the environment of twitteR, tm, wordcloud, dendextend, ggplot2, and Sentimentr packages. This study contributes to the emerging literature on social media analysis. It demonstrates how text mining and sentimental analysis can be used to discover new knowledge about customers. The obtained findings and outcomes of this study should be useful for any managers and organizations willing to use social media analysis in customer recognition.