13
3.3 Network of identified digital trends
The algorithm for internal and Wikipedia related links took an average calculation time of
30 min. In total 1389 undirected links between the trends were detected. The dataset is visualized as a network structure in Figure 4. Additional properties of the nodes, as the size and
color represent the weighted degree and categories of the trend. The position and distance of
the nodes indicates how related these trends are. The trends “artificial intelligence”, “internet
of things“, “machine learning” and “virtual reality mine training” are based in the middle
and act as a central points of the diagram.
The analyzed weighted degree of every single node, shows again, “automation” as a leading trend with 52 relations, followed by “artificial intelligence” (35), “machine learning” (37),
“3D printing” (31) and “virtual reality mine training” (24). This correlates to the positions of
the trends and reflects the central role of these nodes in the network.
3.4 Extracting trends and mine names from research database
The algorithm for analyzing the onemine datatbase were executed on a 4 cores @ 3.4 GHz
and 32 GB machine and took in the average 25 min. In total 2400 paper were analyzed and
25 individual trends in 164 paper were recognized. In the filtered papers, proper name lists
were created and 92 papers with a possible mine name citation were detected. By reviewing
Figure 4. Network structure of all trends with the weighted degree as node size.
3.3 Network of identified digital trends
The algorithm for internal and Wikipedia related links took an average calculation time of
30 min. In total 1389 undirected links between the trends were detected. The dataset is visualized as a network structure in Figure 4. Additional properties of the nodes, as the size and
color represent the weighted degree and categories of the trend. The position and distance of
the nodes indicates how related these trends are. The trends “artificial intelligence”, “internet
of things“, “machine learning” and “virtual reality mine training” are based in the middle
and act as a central points of the diagram.
The analyzed weighted degree of every single node, shows again, “automation” as a leading trend with 52 relations, followed by “artificial intelligence” (35), “machine learning” (37),
“3D printing” (31) and “virtual reality mine training” (24). This correlates to the positions of
the trends and reflects the central role of these nodes in the network.
3.4 Extracting trends and mine names from research database
The algorithm for analyzing the onemine datatbase were executed on a 4 cores @ 3.4 GHz
and 32 GB machine and took in the average 25 min. In total 2400 paper were analyzed and
25 individual trends in 164 paper were recognized. In the filtered papers, proper name lists
were created and 92 papers with a possible mine name citation were detected. By reviewing
Figure 4. Network structure of all trends with the weighted degree as node size.