Social Network Clustering: An Analysis of Gang Networks
نویسندگان
چکیده
In Hollenbeck, a gang-dominated region of Los Angeles, gang activity has been monitored by the LAPD. One manner has been in the form of non-criminal stops. We propose a spectral clustering algorithm to predict gang affiliation from the information obtained from these stops. Despite the sparseness of data, the combination of geography and the record of individuals involved in a stop reveals the underlying gang structure and higher order structures (collaboration or rivalry). Having obtained positive results on the real Hollenbeck data, we then develop methods to create gang simulations that will further our understanding of this algorithm and the situation in Hollenbeck.
منابع مشابه
Detecting Overlapping Communities in Social Networks using Deep Learning
In network analysis, a community is typically considered of as a group of nodes with a great density of edges among themselves and a low density of edges relative to other network parts. Detecting a community structure is important in any network analysis task, especially for revealing patterns between specified nodes. There is a variety of approaches presented in the literature for overlapping...
متن کاملAn “Estimate & Score Algorithm” for simultaneous pa- rameter estimation and reconstruction of missing data on social networks
Dynamic activity involving social networks often has distinctive temporal patterns that can be exploited in situations involving incomplete information. Gang rivalry networks in particular show a high degree of temporal clustering of activity associated with retaliatory behavior. A recent study of a Los Angeles gang network shows that known gang activity between rivals can be modeled as a self-...
متن کاملتشخیص اجتماعات ترکیبی در شبکههای اجتماعی
One of the great challenges in Social Network Analysis (SNA) is community detection. Community is a group of vertices which have high intra connections and sparse inter connections. Community detection or Clustering reveals community structure of social networks and hidden relationships among their constituents. By considering the increase of datasets related to social networks, we need scalabl...
متن کاملAn Adaptive LEACH-based Clustering Algorithm for Wireless Sensor Networks
LEACH is the most popular clastering algorithm in Wireless Sensor Networks (WSNs). However, it has two main drawbacks, including random selection of cluster heads, and direct communication of cluster heads with the sink. This paper aims to introduce a new centralized cluster-based routing protocol named LEACH-AEC (LEACH with Adaptive Energy Consumption), which guarantees to generate balanced cl...
متن کاملAn Artificial Bee Colony Inspired Clustering Solution to Prolong Lifetime of Wireless Sensor Networks
It is very difficult and expensive to replace sensor node battery in wireless sensor network in many critical conditions such as bridge supervising, resource exploration in hostile locations, and wildlife safety, etc. The natural choice in such situations is to maximize network lifetime. One such approach is to divide the sensing area of wireless sensor network into clusters to achieve high ene...
متن کامل