<｜begin▁of▁sentence｜>### Instruction:
As a journal editor, you may encounter a situation where you need to evaluate the influence of specific authors in the academic community. Using networkx, you can import a weighted graph representing the collaboration network of these authors from a file such as example.gml. Then, you can calculate the strength (weighted degree) of individual authors using the strength function in networkx. This will provide valuable insights into the impact and influence of each author within the research community.
### Response:
import igraph as ig

# Reading from an example GML file
g = ig.read('example.gml')

# Calculating the strength for vertex with ID 2
vertex_strength = g.strength(vertices=2, weights='weight', mode='all', loops=True)
print('Strength of vertex 2:', vertex_strength)

# Calculating the strength for multiple vertices, IDs 2, 3, and 5
group_strength = g.strength(vertices=[2, 3, 5], weights='weight', mode='all', loops=True)
print('Strengths of vertices 2, 3, and 5:', group_strength)
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