## 4 Results and Discussions
[109], which investigated Tweets pertaining to Long COVID, a significant limitation of these studies is the restricted temporal scope of the analyzed Tweets. In [108], the examined Tweets were published between 25 March 2022 and 1 April 2022. Similarly, the Tweets analyzed in [109] were published between 11 December 2021 and 20 December 2021. These durations constitute a small portion of the complete timeframe over which Long COVID has had its impact on the global population. This study addresses this limitation by conducting an analysis of Tweets pertaining to Long COVID, published between 25 May 2020 and 31 January 2023. * The application of sentiment analysis to Tweets has proven valuable in discerning the range of views and opinions expressed by the global population on Twitter about vari  
Figure 1.9 Representation of the results of analyses of Tweets to categorize the same into fine-grained sentiment classes. ous subjects of discussion during previous instances of virus outbreaks. Consequently, there has been a notable surge in the volume of literature pertaining to sentiment analysis since the onset of the COVID-19 pandemic. Despite the existence of many studies (e.g., [86; 87; 94; 101; 102; 103; 104; 106; 107]) that have performed sentiment analyses of Tweets pertaining to COVID-19, none of these studies have specifically examined the sentiments expressed in Tweets related to Long COVID. This study addresses this limitation using the Valence Aware Dictionary for Sentiment Reasoning (VADER) methodology to perform sentiment analyses of Tweets about Long COVID. * The examination of conversation patterns of people on Twitter who self-report health-related issues has received significant attention from researchers across a wide range of disciplines. This can be observed through the increasing number of studies that have focused on analyzing such Tweets in the context of mental health [110], autism [111], dementia [112], depression [113], breast cancer [114], swine flu [115], influenza [116], chronic stress [117], post-traumatic stress disorder [118], and dental issues [119]. Since the beginning of the COVID-19 pandemic, scholars in this field, as exemplified by the work of researchers in [99], have redirected their attention toward devising approaches for the acquisition and analysis of Tweets in which individuals willingly disclose how they contracted COVID-19, including self-reported instances of COVID-19. However, previous studies in this area of research did not specifically examine Tweets wherein people self-reported Long COVID. This study addresses this limitation by examining Tweets in which Twitter users self-reported Long COVID. This research demonstrates that the discourse related to Long COVID on Twitter has garnered worldwide interest. The results of this study also indicate that the global population has been proactive in seeking and disseminating information about Long COVID on Twitter. The opinions conveyed by the global population within these online discussions are diverse in terms of the types of opinions as well as the intensity of the opinions expressed. Furthermore, the results suggest variations in the tweeting patterns of the global population while expressing their emotions in this context. As discussed in Section 1, there is presently a lack of pharmacological interventions that have shown efficacy in alleviating or ameliorating the symptoms associated with Long COVID in a randomized-controlled trial (RCT). At the same time, rehabilitation has exhibited effectiveness in managing specific cases of Long COVID. The findings obtained in this study have the potential to provide a foundation for the prompt investigation of the underlying Tweets (positive, negative, or both) by public health agencies. Such an investigation is expected to provide an understanding of the primary worries, needs, or interests of the global population in relation to the self-reporting of Long COVID.