BanglaEmotion is a manually annotated Bangla Emotion corpus, which incorporates the diversity of fine-grained emotion expressions in social-media text. More fine-grained emotion labels are considered such as Sadness, Happiness, Disgust, Surprise, Fear and Anger - which are, according to Paul Ekman (1999), the six basic emotion categories. For this task, a large amount of raw text data are collected from the user’s comments on two different Facebook groups (Ekattor TV and Airport Magistrates) and from the public post of a popular blogger and activist Dr. Imran H Sarker. These comments are mostly reactions to ongoing socio-political issues and towards the economic success and failure of Bangladesh. A total of 32923 comments are scraped from the three sources aforementioned above. Out of these, a total of 6314 comments were annotated into the six categories. The distribution of the annotated corpus is as follows:
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India is a linguistic area with one of the longest histories of contact, influence, use, teaching and learning of English-in-diaspora in the world (Kachru and Nelson, 2006). Thus, a huge number of Indians active on the internet are able in English communication to some degree. India also enjoys huge diversity in language. Apart from Hindi, it has several regional languages that are the primary tongue of people native to the region. This is to the extent that social media including Facebook, WhatsApp, Twitter, etc. contain more than one language, and such phenomena are called code-mixing and code-switching. On the other side, the evolution of sentiments from such social media texts have also created many new opportunities for information access and language technology, but also many new challenges, making it one of the prime present-day research areas. Sentiment analysis in code-mixed data has several real-life applications in opinion mining from social media campaign to feedback analys
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