I have done my masters study research in Sentiment Mining and I have worked on Multi aspect Sentiment Analysis. I want to continue the work in the area, can you help me choosing?
You may concentrate on trending topics in tweets. Tweets which are associated with hash tags are attracting researchers' now a days. Extract trending topics in a specific period, then you can go for opinion mining and sentiment analysis...
Nowadays there are quite a big trend to research on deep learning of NLP and Sentiment Mining , you can follow research work of stanford to get a better understanding and continue your work.
Deep Learning is really popular now. So, first any models where you can use RNN based deep learning systems for sentiment analysis is going to be good.
Now, sentiment analysis is an applied topic. So, you need to find a good interesting data set. As Manoj mentioned, electoral data analysis is good. But, you need to consider am I going to add something new to the field. It cannot just be using Deep Learning methods instead of traditional NLP based methods for electoral data or any data.
You can tak e any Topic Trending Nowadays or Topic on such things that People look out more in social media and look for its reviews online.
Or search for Topics of PHD till now in Sentiment Analysis and its impacts, that might lead you further.
@iqar sana
these are answers listed above which applies to your question too!!
You might be interested in the section outlook 9.3 of my PhD thesis that lists possible research ideas. Thesis Opinion Mining and Lexical Affect Sensing
Moreover, it could be interesting to investigate how computational analysis should consider processing of emotional texts written by authors belonging to different social groups.
Can anyone tell me about the latest and unresolved challenges in App reviews classification? I have to select a thesis topic for my MS research work.
Tarim Nayyab , On Google PlayStore and Apple AppStore there is an issue for developers regarding user reviews: Most of the time, users give 1 star reviews based on their feeling about the content of the app instead of the app, itself. Which in-turn badly effect the ranking of the app.. Developers are regularly looking for such reviews and report them...
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