I'm working on multimodal emotion detection and I'm using a dataset that contains images and text where the two data are related to each other as the posts we are doing on Instagram Facebook which contain a caption that represents the person feelings
Dear Israa K. Salman
These links might be useful, have a look:
1. https://towardsdatascience.com/a-complete-step-by-step-tutorial-on-sentiment-analysis-in-keras-and-tensorflow-ea420cc8913f
2. https://www.analyticsvidhya.com/blog/2018/07/hands-on-sentiment-analysis-dataset-python/
3. https://www.scitepress.org/Papers/2019/79096/79096.pdf
Kind Regards
Qamar Ul Islam
thank you Qamar Ul Islam for the useful links but it also does not contain the dataset that I want even from the research paper I could not find the one which I need
A few non-neural networks b
ased models have achieved significant accuracy in analyzing the sentiment of a corpus. Naive Bayes – Support Vector Machines (NBSVM) works very well when the dataset is very small, at times it worked better than the neural networks based models.
Anything below a score of -0.05 we tag as negative and anything above 0.05 we tag as positive. Anything in between inclusively, we tag as neutral.
10 Popular Datasets For Sentiment Analysis
Hi Israa K. Salman,
Please take a look at (http://www.t4sa.it/); it is a datasets that contains 3 million tweets of both text and images.
Here (https://scholar.google.com/scholar?q=%22t4sa%20it%22%20OR%20%22twitter%20for%20sentiment%20analysis%22) you will find the work that cited this dataset to help you in your ongoing work.
Warm regards,
Mohamed K. Elhadad
C K Gomathy thank you for your reply but these datasets are about only text sentiment analysis
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