###### Abstract  
This paper presents multiple novel findings from a comprehensive analysis of a dataset comprising 1,244,051 Tweets about Long COVID, posted on Twitter between 25 May 2020 and 31 January 2023. First, the analysis shows that the average number of Tweets per month wherein individuals self-reported Long COVID on Twitter was considerably high in 2022 as compared to the average number of Tweets per month in 2021. Second, findings from sentiment analysis using VADER show that the percentages of Tweets with positive, negative, and neutral sentiments were 43.1%, 42.7%, and 14.2%, respectively. To add to this, most of the Tweets with a positive sentiment, as well as most of the Tweets with a negative sentiment, were not highly polarized. Third, the result of tokenization indicates that the tweeting patterns (in terms of the number of tokens used) were similar for the positive and negative Tweets. Analysis of these results also shows that there was no direct relationship between the number of tokens used and the intensity of the sentiment expressed in these Tweets. Finally, a granular analysis of the sentiments showed that the emotion of sadness was expressed in most of these Tweets. It was followed by the emotions of fear, neutral, surprise, anger, joy, and disgust, respectively.  
COVID-19; Long COVID; social media; Twitter; big data; data analysis; natural language processing; data science; sentiment analysis +
Footnote †: journal: _Journal of the Royal Society Interface_  
0000-0002-2000-2000-20000-20000-20000-20000-20000-20000-20000-2  
known as Rhinolophus affinis, dwelling in China's Yunnan Province [7; 8]. An exhaustive investigation into the SARS-CoV-2 genome, alongside its predecessor SARS-CoV, revealed the presence of nearly thirty open reading frames (ORFs) and two unique insertions [9]. Upon scrutinizing the genomes of SARS-CoV and bat coronaviruses, it became apparent to researchers in this field that certain regions, such as ORF6, ORF8, and the S gene, exhibit relatively low levels of sequence similarity across coronaviruses as a whole [10; 11]. Prior works in this field have determined that the interaction between the SARS-CoV-2 S protein and its cell surface receptor, angiotensin-converting enzyme 2 (ACE2), sets in motion the process of viral entry into type II pneumocytes located within the human lung. This vital interaction marks the commencement of the virus's infiltration into the respiratory system. Consequently, the S protein assumes a pivotal and indispensable role in not only the initial transmission but also the persistent and continual infection caused by SARS-CoV-2. In essence, the S protein stands as a linchpin, orchestrating the virus's ability to penetrate the human body and perpetuate its presence [12].  
Although the infection of different organs has been reported in different cases, the SARS-CoV-2 virus usually affects the respiratory systems in patients. Initial research on infections from the SARS-CoV-2 virus in Wuhan, China, has shed light on a variety of symptoms, such as fever, dry cough, difficulty breathing, headache, dizziness, exhaustion, nausea, and diarrhea, that a patient experiences in the first few days of the infection. It is crucial to note that not everyone experiences the same symptoms and that both the extent and severity of these symptoms may vary greatly from individual to individual [13]. After a virus undergoes genetic modifications, it is referred to as having experienced mutations. Because of these genetic alterations, various genetic forms of a virus evolve, which are known as variants. Strains are variants that exhibit differences in their visible traits [14]. The genetic sequences of SARS-CoV-2 were made available to people worldwide on January 10, 2020, by GISAID. Since then, GISAID has made more than 5 million genetic sequences of SARS-CoV-2, obtained from 194 nations and territories, accessible to researchers from different disciplines via their database [15; 16].