The wide reach of social media platforms, such as Twitter, have enabled many users to share their thoughts, opinions and emotions on various topics online. The ability to detect these emotions automatically would allow social scientists, as well as,
businesses to better understand responses from nations and costumers. In this study we introduce a dataset of 30,000 Persian Tweets labeled with Ekman's six basic emotions (Anger, Fear, Happiness, Sadness, Hatred, and Wonder). This is the first publicly available emotion dataset in the Persian language. In this paper, we explain the data collection and labeling scheme used for the creation of this dataset. We also analyze the created dataset, showing the different features and characteristics of the data. Among other things, we investigate co-occurrence of different emotions in the dataset, and the relationship between sentiment and emotion of textual instances. The dataset is publicly available at https://github.com/nazaninsbr/Persian-Emotion-Detection.
Information extraction from documents has become great use of novel natural language processing areas. Most of the entity extraction methodologies are variant in a context such as medical area, financial area, also come even limited to the given lang
uage. It is better to have one generic approach applicable for any document type to extract entity information regardless of language, context, and structure. Also, another issue in such research is structural analysis while keeping the hierarchical, semantic, and heuristic features. Another problem identified is that usually, it requires a massive training corpus. Therefore, this research focus on mitigating such barriers. Several approaches have been identifying towards building document information extractors focusing on different disciplines. This research area involves natural language processing, semantic analysis, information extraction, and conceptual modelling. This paper presents a review of the information extraction mechanism to construct a generic framework for document extraction with aim of providing a solid base for upcoming research.
