138
V. M. Xanat and Y. Toshimasa
Table 10.1 Description of network centralities
Centrality
Definition
Degree
Total number of connections a video has with other videos
Indegree
Number of connections directed to a video
Outdegree
Number of connections a video directs to other videos
Betweenness
Number of shortest paths that connect other videos in the network
by passing through a given video
Closeness
Average number of steps a video requires to access all the other
videos in a network
Clustering Coefficient
Measure of how close is a video to be part of a group
Local Clustering Coefficient Measure of how close is a video to be part of its local group
detect relevant videos and communication hubs. Table 10.1 includes a description
of network centralities employed in the present study. A connection refers to videos
likely to be featured in the recommendation area of YouTube, which are based on
overall viewing patterns, user interactions, playlists, etc.
Also, to compare network centralities across country groups, ANOVA was
computed with Ucinet (Borgatti et al. 2002). Finally, to answer RQ3, qualitative
analysis was performed in top videos in terms of YouTube metrics and network
metrics.
10.3 Results
10.3.1 Types of Design
Table 10.2 shows that English videos from BC countries were more numerous across
design areas but differences were non-significant; while in Spanish, most videos
Table 10.2 Design across country groups
Design area English videos
Spanish videos
BSC
SC BC
BSC
SC BC
Architecture 13
57
915
129
97
157
Industrial D 8
32
180
30
58
46
Graphic D
4
1
59
10
10
17
General
5
7
258
32
20
32
Mixed
4
21
231
38
61
52
Total
34
118 1643 239
246 304
x 2 = 46.981, df = 8, p > 0.05
x 2 = 26.038, df = 8, p < 0.005
V. M. Xanat and Y. Toshimasa
Table 10.1 Description of network centralities
Centrality
Definition
Degree
Total number of connections a video has with other videos
Indegree
Number of connections directed to a video
Outdegree
Number of connections a video directs to other videos
Betweenness
Number of shortest paths that connect other videos in the network
by passing through a given video
Closeness
Average number of steps a video requires to access all the other
videos in a network
Clustering Coefficient
Measure of how close is a video to be part of a group
Local Clustering Coefficient Measure of how close is a video to be part of its local group
detect relevant videos and communication hubs. Table 10.1 includes a description
of network centralities employed in the present study. A connection refers to videos
likely to be featured in the recommendation area of YouTube, which are based on
overall viewing patterns, user interactions, playlists, etc.
Also, to compare network centralities across country groups, ANOVA was
computed with Ucinet (Borgatti et al. 2002). Finally, to answer RQ3, qualitative
analysis was performed in top videos in terms of YouTube metrics and network
metrics.
10.3 Results
10.3.1 Types of Design
Table 10.2 shows that English videos from BC countries were more numerous across
design areas but differences were non-significant; while in Spanish, most videos
Table 10.2 Design across country groups
Design area English videos
Spanish videos
BSC
SC BC
BSC
SC BC
Architecture 13
57
915
129
97
157
Industrial D 8
32
180
30
58
46
Graphic D
4
1
59
10
10
17
General
5
7
258
32
20
32
Mixed
4
21
231
38
61
52
Total
34
118 1643 239
246 304
x 2 = 46.981, df = 8, p > 0.05
x 2 = 26.038, df = 8, p < 0.005