@inproceedings{3a61ea66138e40029845db0ad93f6c7d,
title = "A Study of Sentiment Analysis Approaches in Short Text",
abstract = "Recently, the remarkable growth of Internet technology, particularly on social media networking sites, enables gathering data for analyzing and gaining insights. It is challenging to analyze such a huge amount of information that causes time-consuming. So, it is necessary to make an intelligent system that automatically analyzes a great amount of data. Sentiment analysis methods appear to analyze sentiments and opinions of people through what they write on social networking sites. Different sentiment analysis approaches have been proposed to understand the sentiments and opinions expressed by the individuals in the text. However, some methods produce an improper result when applied to short text due to text briefness and sparsity. In this paper, we present sentiment analysis models that analyzing people feelings and opinions in the short text such as tweets and instant messages. Then, we illustrate the evaluation metrics used to assess the quality of the generated hierarchical structure in extracting an ideal tree.",
keywords = "Evaluation methods, Hierarchical structure, Sentiment analysis, Short text",
author = "Ibrahim, \{Ahmed F.\} and M. Hassaballah and Ali, \{Abdelmgeid A.\} and Ibrahim, \{Ibrahim A.\}",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 2nd World Conference on Internet of Things: Applications and Future, ITAF 2020 ; Conference date: 16-12-2020 Through 17-12-2020",
year = "2022",
doi = "10.1007/978-981-16-2275-5\_8",
language = "English",
isbn = "9789811622748",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "143--151",
editor = "Magdi, \{Dalia A.\} and Helmy, \{Yehia K.\} and Mohamed Mamdouh and Amit Joshi",
booktitle = "Digital Transformation Technology - Proceedings of ITAF 2020",
address = "Germany",
}