Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: EMH: Extended Mixing H-index centrality for identification important
  users in social networks based on neighborhood diversity   The rapid expansion of social network provides a suitable platform for users
to deliver messages. Through the social network, we can harvest resources and
share messages in a very short time. The developing of social network has
brought us tremendous conveniences. However, nodes that make up the network
have different spreading capability, which are constrained by many factors, and
the topological structure of network is the principal element. In order to
calculate the importance of nodes in network more accurately, this paper
defines the improved H-index centrality (IH) according to the diversity of
neighboring nodes, then uses the cumulative centrality (MC) to take all
neighboring nodes into consideration, and proposes the extended mixing H-index
centrality (EMH). We evaluate the proposed method by
Susceptible-Infected-Recovered (SIR) model and monotonicity which are used to
assess accuracy and resolution of the method, respectively. Experimental
results indicate that the proposed method is superior to the existing measures
of identifying nodes in different networks.

32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
2
The categories of this paper are: math
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga