**4. Discussion: Main Clusters on Legaltech**

To analyze in which scientific fields or research clusters Legaltech-related works are present, a scientific community detection software, vosviewer, has been used (Van Eck and Waltman 2010). This software has proven to be useful in the analysis of many fields of knowledge such as medicine (Garrido-Cardenas et al. 2020), social sciences (Muyor-Rodriguez et al. 2019) or engineering (Salmeron-Manzano and Manzano-Agugliaro 2018). Thus, Figure 3 was obtained. This figure shows 4 different clusters that currently exist in the scientific literature, which can be distinguished according to the different colors of each one. The clusters are linked by the common keywords of all the documents analyzed. For each cluster, the main associated keywords are summarized in Table 3, and finally, a name is given to encompass the topic of each cluster.

**Figure 3.** Main clusters detected on Legaltech documents.


The first cluster is focused on computer science as verified by the main keywords involved: Algorithms, artificial intelligence, law, legal tech, legal technologies, machine learning, natural language processing. Regarding Artificial Intelligence, the first paper in this regard was "Can the mechanization of law triumph over lawyers?" from 2017 (Fortuit and Hamidou 2017), should be highlighted. The use of machine learning (ML) techniques for legal analysis and decision making in the U.S. judicial system has recently been analyzed (Delgado 2019), concluding how ML came to be adopted as a standard tool for automating fact discovery for high-stakes civil litigation.

Regarding natural language processing (NLP), there are five areas of legal activity where NLP is playing an increasing role (Dale 2019):


The second cluster is focused on Justice, as evidenced by the main keywords involved: Access to justice, design thinking, law students, rule of law. Within this topic there are works within what one could classify as philosophy of law, who argue that advances in equal access to justice and the rule of law lie primarily in the introduction of lawyers' own cognitive operations in contexts where human lawyers cannot be deployed for purely economic reasons (Gowder 2018).

The third cluster is focused on the legal profession, as can be seen from the main keywords involved: Legal profession, legal services, neo-liberalism, professional regulation. Within the field of legal services, it is worth mentioning the analysis of automated Online Dispute Resolution (ODR), where 3 cases can be identified (Barnett and Treleaven 2018):


The fourth cluster is focused on Legal design as evidenced by the main keywords involved: Blockchain, legal design, smart contract. The blockchain technology has several legal consequences and the one with the greatest need for legal regulation are cryptocurrencies such as bitcoins (Salmeron-Manzano 2017). Legal design aims to apply human-centered design to the world of law, to make legal systems and services more human-centered, usable, and satisfying (Hagan 2017). In short, legal Design is an interdisciplinary approach to apply human-centered design to prevent or solve legal problems. The legal design manifesto is available on-line (LeDA 2021). On the other hand, "smart contract" means the specific use of the use of software code to formulate, check and enforce an agreement between contracting agents (Salmerón-Manzano and Manzano-Agugliaro 2019).

The fifth cluster is centered on Law firms as evidenced by the main keywords involved: Law firms, legal technique, legal technology. Law firms are increasingly adopting digital technologies to make their work more efficient as opposed to traditional work methods. The business model of many law firms, like the legal professions as a large whole, will face a significant paradigm shift, as the work provided by law firms in the form of billable hours largely consists of services that do not require higher legal training, but involve mere data processing (Kerikmäe et al. 2018).

The sixth cluster is focused on Legal Education as evidenced by the main keywords involved: Legal education, legal regulation, vocational training. Anticipated changes in the training needs of lawyers and solicitors present a challenge to law schools to revise their curricula (Ryan 2020). Thus, as the legal profession begins to seriously deploy digital technology in the delivery of services and information, more law schools are including technology education in their curricula (Jackson 2016).

The evolution of the concepts related to Legaltech are shown in Figure 4. The colors represent the evolution over time, with blue being the oldest and red the most modern. It can only be seen in the last two years of the study, observing how it evolves from law firms and rule of law at the beginning of 2018, to artificial intelligence or machine learning,

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i.e., incorporating technologies from computer science. The most occurrence of Legaltech related terms is mostly in 2019. See for example, legal profession, professional regulation, legal services, legal regulation, vocational training, access to justice or law students.

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**Figure 4.** Evolution of subjects related to Legaltech.

Regarding the concept itself, it can be seen that at the beginning it was legal technology, later legal tech, and finally it has been coined as a term in itself Legaltech. Legaltech appears as an author keyword, according to WoS, in 2017, with no previous records found.
