Department of Foreign Language, Zhanjiang University of Science and Technology, Zhanjiang 524000, China.
J Environ Public Health. 2022 Sep 2;2022:1502959. doi: 10.1155/2022/1502959. eCollection 2022.
With the rapid development of society, the emergence and innovation of network buzzwords continue to emerge. On the rapidly changing social network platform, previous sentiment analysis tasks cannot fully meet the needs of users. This paper aims to study the metaphorical function and affective cognition in Internet English loanwords. This paper proposes a neural network algorithm and conducts a comprehensive analysis of the metaphorical function and emotional cognition of Internet English loanwords. The neural network algorithm has a powerful sentiment analysis function, so the article chooses this algorithm. The experimental results of this paper show that with the popularity of the Internet, more and more people go online. In 2013, the proportion of Internet users was the highest at 23.2%. In 2015, the proportion of Internet users was 38.3%, an increase of 15.1% in just one year. The percentage of people online will reach 68.3% by 2021, indicating that almost half of the people have learned to surf the Internet. This also means that Internet English loanwords have also been developed. The rapid development of loanwords in Internet English is because they have metaphorical functions and express people's emotions.
随着社会的快速发展,网络热词的出现和创新不断涌现。在快速变化的社交网络平台上,以前的情感分析任务不能完全满足用户的需求。本文旨在研究网络英语外来词的隐喻功能和情感认知。本文提出了一种神经网络算法,并对网络英语外来词的隐喻功能和情感认知进行了全面分析。神经网络算法具有强大的情感分析功能,因此本文选择了该算法。本文的实验结果表明,随着互联网的普及,越来越多的人上网。2013 年,互联网用户的比例最高,为 23.2%。2015 年,互联网用户的比例为 38.3%,仅一年就增长了 15.1%。到 2021 年,上网人数将达到 68.3%,这意味着几乎一半的人已经学会了上网。这也意味着网络英语外来词也在发展。网络英语外来词的快速发展是因为它们具有隐喻功能,可以表达人们的情感。