Analyzing User Digital Emotions from a Holy versus Non-Pilgrimage City in Saudi Arabia on Twitter Platform

Humans are the product of what society and their environment conditions them into being. People living in metropolitan cities have a very fast-paced life constantly exposed to different situations. A social media platform enables individuals express emotions sentiments thus acts as reservoir for digital emotion footprints its users. This study proposes that user data available on Twitter has potential showcase contrasting people residing pilgrimage city versus those other, non-pilgrimage areas. We collected Arabic geolocated tweets users Mecca (holy city) Riyadh (non-pilgrimage city). The were classified basis Plutchik’s eight basic categories, Fear, Anger, Sadness, Joy, Surprise, Disgust, Trust, Anticipation. new bilingual dictionary, AEELex (Arabic English Emotion Lexicon), was designed determine derived from tweets. been validated commonly known popular lexicons. An analysis revealed had more positivity than Riyadh. Anticipation dominant or most expressed both places. However, larger proportion fell under this category. proposed an initial attempt toward studying emotional behavioral differences between Saudi Arabia. several other important applications. First, emotion-based could contribute development machine learning-based model predicting depression netizens. Second, appearances mined text benefit efforts identify regional location particular user.