Şeyma - Tweet Data Analysis

Summarization

This series of tweets discuss various topics such as police, Tik Tok videos, violence, Süleyman veli, Rönesans Rezidans, Beşiktaş, shame, Arda Güler, Tik Tok, Selçuk Bayraktar, Suriye, Ahbap, Yağma, HadiniBilLûbeAyar, Ülkü Ocakları, Çarşı, Meral Akşener, Yakalandı, Deprem bölgesi, Nene Hatunları, Hatay, Adıyaman, Esad, Haluk Levent, Gerçek Kahramanlar, TahaDuymaza, Gamze Özçelik, İstifa, Oğuzhan Uğur, Arzu Apartmanı, Birlikte Güçlüyüz, İskenderun Devlet Hastanesi, Cadır İhtiyacı, Beşiktaş Çarşı, yardım tırı, Yakalandılar, karaktersiz şerefsizler, hırsızlık, yakalanan kadın. It also focuses on topics such as assisting people in need, not forgetting true heroes, and the consequences of acts like vandalism, theft and violence.

Topic Modeling

1. Natural disasters and emergency responses
2. Crime and criminality
3. Corruption and selfless acts
4. Socio-political issues and activism
5. Cultural and social subjects

Emotional Analysis

The tweets express a range of emotions including shock, sadness, anger, shame, and fear. The tweets also convey a sense of empathy for those affected by violence, natural disasters, and theft. There is also a sense of admiration for those who are selfless and caring towards others. Finally, there is a sense of disgust and disapproval towards those who are greedy and selfish.

Trend Analysis

1. Police/Law enforcement
2. Natural disasters (i.e. earthquakes)
3. Violence/Domestic abuse
4. Economic issues (i.e. financial crime, speculative trading etc.)
5. Generational and societal issues (i.e. generational gap, charity, equality etc.)