Analysis of tweets on toothache during the COVID-19 pandemic using the CrystalFeel algorithm: a cross-sectional study - Halenur Altan; Alem Coşgun (BMC, 2021)
Abstract Background Reasons such as the lack of information on the COVID-19 disease, lack of proven treatment for it, uncertainty about the duration of the pandemic, or social isolation affect people's mental health. This study aimed to analyze the emotional type and intensity in tweets on toothache posted during the COVID-19 pandemic. Methods Using the Twitter Search API, we collected tweets in English associated with the keywords "Corona, Toothache" "Corona, Tooth, Pain" "Corona, Dental Pain" "Covid-19, Toothache" "Covid-19, Tooth, Pain" and "Covid-19, Dental Pain" posted between March 11, 2020 and June 30, 2020 all around the world. After the relevant inclusion and exclusion criteria were applied, 426 posts were selected and analyzed using the CrystalFeel algorithm, a sensitivity analytical technology with proven accuracy. The chi-square test (SPSS v23, IBM) was used to compare emotions and emotional intensities according to the words used. Results It was determined that 80.3% of the participants experienced fear and 61.7% had a negative emotional intensity. There was no statistically significant difference between the distributions of emotions according to the words without time distinction (p = 0.136). There was a statistically significant difference between the distributions of emotional intensity according to the words without time distinction (p = 0.006). The keyword "Corona, Toothache" was used the most frequently by 30.8% of the participants. Conclusions This study is the first to analyze the emotional reactions of individuals who experienced toothaches during the COVID-19 pandemic using the CrystalFeel algorithm. Monitoring the social media posts of individuals experiencing toothache during the pandemic will help reduce fear and anger emotions and design public information messages that are compatible with the target group's needs.