Nandwani Pansy, Verma Rupali
Computer Science and Engineering Department, Punjab Engineering College, Chandigarh, India.
Soc Netw Anal Min. 2021;11(1):81. doi: 10.1007/s13278-021-00776-6. Epub 2021 Aug 28.
Social networking platforms have become an essential means for communicating feelings to the entire world due to rapid expansion in the Internet era. Several people use textual content, pictures, audio, and video to express their feelings or viewpoints. Text communication via Web-based networking media, on the other hand, is somewhat overwhelming. Every second, a massive amount of unstructured data is generated on the Internet due to social media platforms. The data must be processed as rapidly as generated to comprehend human psychology, and it can be accomplished using sentiment analysis, which recognizes polarity in texts. It assesses whether the author has a negative, positive, or neutral attitude toward an item, administration, individual, or location. In some applications, sentiment analysis is insufficient and hence requires emotion detection, which determines an individual's emotional/mental state precisely. This review paper provides understanding into levels of sentiment analysis, various emotion models, and the process of sentiment analysis and emotion detection from text. Finally, this paper discusses the challenges faced during sentiment and emotion analysis.
在互联网时代的快速发展下，社交网络平台已成为向全世界传达情感的重要手段。一些人使用文本内容、图片、音频和视频来表达他们的感受或观点。另一方面，通过基于网络的社交媒介进行文本交流有些让人应接不暇。由于社交媒体平台，互联网每秒都会产生大量的非结构化数据。必须在数据生成时尽快对其进行处理，以理解人类心理，这可以通过情感分析来实现，情感分析能够识别文本中的极性。它评估作者对某个事物、管理、个人或地点持消极、积极还是中立的态度。在某些应用中，情感分析是不够的，因此需要进行情绪检测，情绪检测能精确地确定一个人的情绪/心理状态。这篇综述文章介绍了情感分析的层次、各种情绪模型以及从文本中进行情感分析和情绪检测的过程。最后，本文讨论了情感和情绪分析过程中面临的挑战。
