# Algorithms in Low-Code-No-Code for Research Applications: A Practical Review
## 6 Demonstration of LCNC Adoption in Modern Research
were translated into English, and sentiment analysis was performed to ascertain whether these posts were negative, positive, or neutral. Moreover, locations mentioned on these posts were extracted using NER. As previously mentioned in Section 5, Microsoft Cognitive Services Text Analytics API [75] were used for translation, sentiment analysis, and NER on these Tweets. As seen from Figures 3 and 4, only drag-and-drop features provided by the cloud-based LCNC platforms were used to collect and analyze the data. After collecting the data, they were analyzed using complex AI-based algorithms, such as CNN (as shown in Figure 5). Finally, in Figure 6, we can see the interactive dashboard visualizing the entire dataset from 11 October 2022 to 13 November 2022. The dashboard in Figure 6 shows different types of cyber-attacks, such as ransomware, exploit, spam, and others, and a user can click any of these types and the dashboard will filter itself automatically based on the selected type. Moreover, a user can click on any country and the entire dashboard will be filtered to represent data pertaining to the selected country. The global cyber-attack data collection as shown in Figure 3 and Table 1 (within Appendix A) was deployed in mobile and tablet contexts, as shown in Figures 7 and 8, respectively. In Figure 7, the solution was deployed on a Samsung Galaxy Note 10 Lite mobile. On the other hand, Figure 8 shows the deployment on an Apple iPad, 15 th generation. None of this deployment required any high-level or low-level coding skills from the researchers. As mentioned earlier, the cyber intelligence solution was developed using Microsoft Power Platform. All the source files (including the pbix Microsoft Power BI solution, cyber-related Tweets, etc.) are publicly available at [[https://github.com/[PERSON]/COVID_Index_Anomaly](https://github.com/[PERSON]/COVID_Index_Anomaly)]([https://github.com/[PERSON]/COVID_Index_Anomaly](https://github.com/[PERSON]/COVID_Index_Anomaly)) (accessed on 3 January 2023) for the sake of research reproducibility. Figure 6: Visualization of cyber-attack data on Microsoft Power BI [49] without writing a single line of code. As seen in this section, using the LCNC platform. a researcher can easily obtain data from multiple sources (e.g., social media, online news sites, online databases), and apply AI algorithms to deploy not only a cyber intelligence solution, but also political threat intelligence, COVID-19 intelligence, social cohesion intelligence, military intelligence, and many other innovative solutions. ## 7 Conclusions

Within this paper, several existing studies that used modern LCNC platforms were reviewed and analyzed. Since adoption of LCNC platforms for solving research questions is still at the level of infancy, only 47 studies of scientific significance were found. Among there studies, 3 were LCNC review articles, 21 were LCNC feature-related articles, and only 23 were on multidisciplinary research solving research questions with LCNC platforms. With these 23 LCNC platform related studies, researchers used 6 different LCNC platforms

Figure 8: Global cyber-attack data along with cyber-related social media data being shown on a deployed iOS App on an Apple iPad, ninth generation. Figure 7: Global cyber-attack data of different types are demonstrated on a deployed Android app on a Samsung Galaxy Note 10 Lite Mobile. (e.g., SetXRM, the vf-OS platform, Aurea BPM, CRISP-DM, Primary AI, Microsoft Power Platform). A total of 61% (i.e., 14 out of 23) of these existing studies resorted to Microsoft Power Platform as their chosen LCNC platform. These studies predominantly used 14 features of modern LCNC platforms as depicted in Table 3 to solve different research problems. These research problems were within the area of global news analysis, social media analysis, landslides, tornadoes, COVID-19, digitization of processes, manufacturing, logistics, supply chain management, AI education, industrial engineering education, and software/app development (as shown in Table 4).