Tunca Sezai, Sezen Bulent, Wilk Violetta
Faculty of Business Administration, Gebze Technical University, Kocaeli, Turkey.
School of Business and Law, Edith Cowan University, Joondalup, Perth, WA Australia.
J Big Data. 2023;10(1):82. doi: 10.1186/s40537-023-00773-w. Epub 2023 May 28.
The metaverse has become one of the most popular concepts of recent times. Companies and entrepreneurs are fiercely competing to invest and take part in this virtual world. Millions of people globally are anticipated to spend much of their time in the metaverse, regardless of their age, gender, ethnicity, or culture. There are few comprehensive studies on the positive/negative sentiment and effect of the newly identified, but not well defined, metaverse concept that is already fast evolving the digital landscape. Thereby, this study aimed to better understand the metaverse concept, by, firstly, identifying the positive and negative sentiment characteristics and, secondly, by revealing the associations between the metaverse concept and other related concepts. To do so, this study used Natural Language Processing (NLP) methods, specifically Artificial Intelligence (AI) with computational qualitative analysis. The data comprised metaverse articles from 2021 to 2022 published on The Guardian website, a key global mainstream media outlet. To perform thematic content analysis of the qualitative data, this research used the Leximancer software, and the The Natural Language Toolkit (NLTK) from NLP libraries were used to identify sentiment. Further, an AI-based Monkeylearn API was used to make sectoral classifications of the main topics that emerged in the Leximancer analysis. The key themes which emerged in the Leximancer analysis, included "metaverse", "Facebook", "games" and "platforms". The sentiment analysis revealed that of all articles published in the period of 2021-2022 about the metaverse, 61% (n = 622) were positive, 30% (n = 311) were negative, and 9% (n = 90) were neutral. Positive discourses about the metaverse were found to concern key innovations that the virtual experiences brought to users and companies with the support of the technological infrastructure of blockchain, algorithms, NFTs, led by the gaming world. Negative discourse was found to evidence various problems (misinformation, harmful content, algorithms, data, and equipment) that occur during the use of Facebook and other social media platforms, and that individuals encountered harm in the metaverse or that the metaverse produces new problems. Monkeylearn findings revealed "marketing/advertising/PR" role, "Recreational" business, "Science & Technology" events as the key content topics. This study's contribution is twofold: first, it showcases a novel way to triangulate qualitative data analysis of large unstructured textual data as a method in exploring the metaverse concept; and second, the study reveals the characteristics of the metaverse as a concept, as well as its association with other related concepts. Given that the topic of the metaverse is new, this is the first study, to our knowledge, to do both.
元宇宙已成为近年来最流行的概念之一。公司和企业家们正在激烈竞争,以投资并参与这个虚拟世界。预计全球数百万人将在元宇宙中度过大量时间,无论其年龄、性别、种族或文化如何。对于这个新出现但定义尚不明确、已迅速改变数字格局的元宇宙概念,很少有全面的研究探讨其积极/消极情绪及影响。因此,本研究旨在更好地理解元宇宙概念,首先识别其积极和消极情绪特征,其次揭示元宇宙概念与其他相关概念之间的关联。为此,本研究使用了自然语言处理(NLP)方法,特别是结合计算定性分析的人工智能(AI)。数据包括2021年至2022年发表在全球主要主流媒体《卫报》网站上的关于元宇宙的文章。为了对定性数据进行主题内容分析,本研究使用了Leximancer软件,并用NLP库中的自然语言工具包(NLTK)来识别情绪。此外,基于AI的Monkeylearn API被用于对Leximancer分析中出现的主要主题进行部门分类。Leximancer分析中出现的关键主题包括“元宇宙”“脸书”“游戏”和“平台”。情绪分析显示,在2021 - 2022年期间发表的所有关于元宇宙的文章中,61%(n = 622)为积极,30%(n = 311)为消极,9%(n = 90)为中性。关于元宇宙的积极论述涉及虚拟体验在区块链、算法、非同质化代币(NFT)等技术基础设施支持下给用户和公司带来的关键创新,其中游戏领域起了引领作用。消极论述则表明在脸书和其他社交媒体平台使用过程中出现的各种问题(错误信息、有害内容、算法、数据和设备),以及个人在元宇宙中受到伤害或元宇宙产生新问题。Monkeylearn的研究结果显示“营销/广告/公关”角色、“娱乐”业务、“科技”活动是关键内容主题。本研究的贡献有两方面:第一,它展示了一种全新的方法,将对大量非结构化文本数据的定性数据分析进行三角测量,作为探索元宇宙概念的一种方法;第二,该研究揭示了元宇宙作为一个概念的特征,以及它与其他相关概念的关联。鉴于元宇宙这一主题是新的,据我们所知,这是第一项同时做到这两点的研究。