Abstract
The growth and popularity of social media platforms have generated a new social interaction environment thus a new collaboration and communication network among individuals. These platforms own tremendous amount of data about users’ behaviors and sentiments since people create, share or exchange their information, ideas, pictures or video using them. One of these popular platforms is Twitter, which via its voluntary information sharing structure, provides researchers data potential of benefit for their studies. Based on Twitter data, in this study a multilingual sentiment detection framework is proposed to compute European Gross National Happiness (GNH). This framework consists of a novel data collection, filtering and sampling method, and a newly constructed multilingual sentiment detection algorithm for social media big data, and tested with nine European countries (United Kingdom, Germany, Sweden, Turkey, Portugal, The Netherlands, Italy, France and Spain) and their national languages over a six year period. The reliability of the data is checked with peak/troughs comparison for special days from Wikipedia news lists. The validity is checked with a group of correlation analyses with OECD Life Satisfaction survey reports’, Euro-Dollar and other currency exchanges, and national stock market time series data. After validity and reliability confirmations, the European GNH map is drawn for six years. The main problem addressed is to propose a novel multilingual social media sentiment analysis framework for calculating GNH for countries and change the way of OECD type organizations’ survey and interview methodology. Also, it is believed that this framework can serve more detailed results (e.g., daily or hourly sentiments of society in different languages).
Highlights
Introduction & Literature ReviewThe rise of social broadcasting technologies has led to open data access for researchers
The user Twitter features such as follower count, friends count, Twitter age, number of Tweets have not been taken into account yet in terms of possible relations of them
Results showed that all the Gross National Happiness (GNH)-TD of countries are significantly correlated with monetary exchanges and stock market indices
Summary
Introduction & Literature ReviewThe rise of social broadcasting technologies has led to open data access for researchers. The use of social media has diffused widely in society with recent statistical data showing high penetration rates [3,4,5,6]. Quan-Haase and Young [7] users tend to embrace new media and adopt them as part of their communication repertoire To some degree this is an advantage at the current stage of studying social media, as it leaves much room for exploring approaches to address research questions [8,9].
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