# Smart Textiles: A Review and Bibliometric Mapping
## 3 Results and Discussion
### Originality and Limitations of the Study  
To the best of our knowledge, this study is the first attempt to provide a comprehensive bibliometric analysis in the domain of smart textiles, using terminology, definitions, and categorization of different types of smart textiles and textile products according to the standard ISO/TS 23383. This served as the basis for the selection of keywords for further analyses, for the extraction of the document sample from the Scopus database, for the bibliometric analyses using VOSviewer (v1.6.19) and Bibliometrix (v4.3.0)/ Biblioshiny (v4.1) as tools for science mapping, and for content analysis and review.  
Accordingly, the novelty and value of this paper is to provide a new comprehensive overview of the smart textiles research field, to better understand the core knowledge structure of the research domain, to highlight the key research areas and directions, to provide researchers with a broader insight into new technologies, materials, and products, to identify knowledge gaps and develop new research ideas, and to position their own research contributions in the smart textiles landscape.  
It is important to mention some limitations to the present study. First, a science map cannot represent more than what is contained in the data on which it is based. The literature data sources for this study were, after several search queries in different databases, limited to the Scopus database. The inclusion of other databases, such as Web of Science, Google  
Figure 13: Countries’ collaboration world map in smart textiles research.  
Scholar, or patent databases like Espacenet, could have potentially uncovered further insights not included in this study. Second, we may have missed some articles that did not use searched keywords in the abstract, title, or keyword fields. In addition, we did not include grey literature or articles published in languages other than English in our analysis.  
The nature of the bibliometric methodology is also a limitation in itself. In particular, because bibliometric analysis is quantitative in nature, the qualitative conclusions of bibliometrics can be quite subjective, and the relationship between quantitative and qualitative results may be unclear [244].  
[PERSON] [82] discussed the objectivity of science maps. The creation of science maps involves several methodological and technical decisions from the science cartographer, such as the unit of analysis, the mapping technique, the normalisation method, the visualisation approach, the clustering algorithm, and so on, and each decision affects the results [82]. These decisions in the science map workflow should be transparent in order to warrant the reproducibility of science maps [245].  
Several authors [58; 59; 246] also recommended using co-word analysis in combination with co-citation analysis (past) or bibliographic coupling (present) to enrich understanding and interpretations of thematic clusters, to gain additional insights into the dynamics of the field and to predict forthcoming trajectories.  
However, in this study, we have considered and used as many recommendations from authors in the field of bibliometrics as possible, so we consider the presentation to be comprehensive and integrated.