1. Kim YE, Schmidt EM, Migneco R, Morton BG, Richardson P, Scott JJ, Speck JA, Turnbull D (2010) State of the art report: music emotion recognition: a state of the art review. In: Stephen Downie J, Veltkamp RC (eds) Proceedings of the 11th International Society for Music Information Retrieval Conference, ISMIR 2010, Utrecht, Netherlands, August 9–13, 2010. International Society for Music Information Retrieval, pp 255–266
2. Acheampong FA, Wenyu C, Nunoo-Mensah H (2020) Text-based emotion detection: advances, challenges, and opportunities. Eng Rep 2(7):e12189
3. Shivhare SN, Khethawat S (2012) Emotion detection from text. In: Proceedings of International workshop on Data Mining & Knowledge Management Process (DKMP-2012), New Delhi, India, August 26–27, 2012, vol 2. Computer Science Conference Proceedings (CSCP), pp 371–377
4. Bogdanov D, Porter A, Tovstogan P, Won M (2019) Mediaeval 2019: emotion and theme recognition in music using jamendo. In: Larson MA, Hicks SA, Constantin MG, Bischke B, Porter A, Zhao P, Lux M, Quiros LC, Calandre J, Jones G (eds) Working Notes Proceedings of the MediaEval 2019 Workshop, Sophia Antipolis, France, 27–30 October 2019, volume 2670 of CEUR Workshop Proceedings. CEUR-WS.org
5. Shakoor AA, Sahebdin WB, Pudaruth S (2015) Exploring the evolutionary change in bollywood lyrics over the last two decades. In: The Second International Conference on Data Mining, Internet Computing, and Big Data (BigData2015), Reduit, Mauritius