{'fraction_non_alphanumeric': 0.02145922746781116, 'fraction_numerical': 0.0, 'mean_word_length': 4.913043478260869, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Subjective well-being prediction from social networks: A review

From the ancient times, every human being has been trying to improve themselves, either for personal or societal benefits. These benefits define the well-being of individuals. Well-being can be judged by outer and inner factors. The outer factors can be in the form of materials and it can measure by objective factors like GDP (Gross Development Product). The internal components are the feelings of a person which characterize how life is experienced by a person. The personal satisfaction (Quality of Life, QoL) is the detecting of people day by day life including all enthusiastic, social, and physical viewpoints. QoL is for the most part measured by requesting that individuals report their joy and life fulfillment. The measurement of emotions in the human behavior in terms of happiness is known as Subjective Well-Being (SWB). In this wireless age, people express their emotions on social networking sites (SNs). The expressions are largely in text form and the growing importance of linguistic text analysis of SNs gives a direction to predict the SWB of individuals. The paper presents the main findings from the literature on various determinants of happiness. The major theories have been studied and their parameters to measure the human behavior from the SWB perspective are defined. Also, this paper describes how these parameters have been used by researchers to predict SWB from SNs. The effectiveness in predicting the SWB from SNs has been elaborated and the positive, and negative effects of SNs usage on individual behavior have been discussed.