
Data analysis is the process of extracting insights from data. Data is heterogeneous in all ways, and processing such data is a challenge. Before applying any machine learning model to any datasets, it is necessary to understand the problem, deal with the missing values and noise, visualize the dataset, and to select the machine learning model to analyze the data. Following is an attempt to highlight the techniques of data analysis.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
