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Predicting defects using change genealogies
2013
2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE)
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prediction models not only show better classification accuracies as models based on code complexity, but can also outperform classification models based on code dependency network metrics. ...
To this end, we group changes into change genealogies, graphs of changes reflecting their mutual dependencies and influences and develop new metrics to capture the spatial and temporal influence of changes ...
TABLE III STRUCTURAL III HOLES METRICS SIMILAR TO BURT
TABLE IV PROJECTS IV USED FOR EXPERIMENTS. ...
doi:10.1109/issre.2013.6698911
dblp:conf/issre/HerzigJRZ13
fatcat:vyg7jjib6bdj7dvkweoayuwdci
Predicting Client Satisfaction through (E-Mail) Network Analysis: The Communication Score Card
[article]
2013
arXiv
pre-print
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This study seeks to better understand the network characteristics of client support teams by analyzing the teams' e-mail communication networks and comparing it to client organization's satisfaction. ...
In particular, we found that social network metrics correlate with client satisfaction as measured by Net Promoter Score (NPS). ...
By continuously tracking changes in network structure and dynamics, service providers might be able to act faster and manage projects more easily. ...
arXiv:1308.1164v1
fatcat:jjwrztwhbvetzc4axl3jc5u2ne
Community-Driven Social Influence Analysis and Applications
[chapter]
2015
Lecture Notes in Computer Science
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As a next step, we intend to detect users that act as structural hole spanners and analyze their social influence across different communities. ...
In this PhD project, we aim to study users' social influence at the community level, mainly because users in social networks are naturally organized in communities and communities play fundamental roles ...
To discover structural hole spanners from the social network, Lou and Tang [9] have proposed two algorithms which are purely based on graph structure. ...
doi:10.1007/978-3-319-19890-3_48
fatcat:m27ufbm4p5holbeuw7yl4lflxu
Predicting defects using network analysis on dependency graphs
2008
Proceedings of the 13th international conference on Software engineering - ICSE '08
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In this paper, we propose to use network analysis on these dependency graphs. This allows managers to identify central program units that are more likely to face defects. ...
In our evaluation on Windows Server 2003, we found that the recall for models built from network measures is by 10% points higher than for models built from complexity metrics. ...
between dependencies and defects. ...
doi:10.1145/1368088.1368161
dblp:conf/icse/ZimmermannN08
fatcat:wjsdbofmnve6xgqjv3ryietovm
Standing out in a networked communication context: Toward a network contingency model of public attention
2020
New Media & Society
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the network structure of the communication context. ...
This study takes a strategic network perspective and draws from recent research in network science to propose the network contingency model of public attention. ...
from acting because of its ties to others), structural hole effectiveness (the effective size of a node's ego network based on redundancy of ties), and structural hole efficiency (the fraction of nodes ...
doi:10.1177/1461444820939445
fatcat:ezlotos7gfdtbknwn6k7vuknhq
Innovation networks: the effects of collaboration in the oil and gas industries
2017
International Journal of Auditing Technology
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collaboration affects patent productivity given network metrics such as centrality, structural holes, and hierarchy. ...
They are valid and can contribute to management activities, although they cannot predict the productivity of an innovation network. ...
However, although BP, Shell, Sinopec, and Total are among the seven companies with the greatest revenues, they are insufficient to represent the whole oil and gas industries. ...
doi:10.1504/ijaudit.2017.10007797
fatcat:skrnvyjrsfaojor7zxaksbdj6q
Innovation networks: the effects of collaboration in the oil and gas industries
2017
International Journal of Auditing Technology
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collaboration affects patent productivity given network metrics such as centrality, structural holes, and hierarchy. ...
They are valid and can contribute to management activities, although they cannot predict the productivity of an innovation network. ...
However, although BP, Shell, Sinopec, and Total are among the seven companies with the greatest revenues, they are insufficient to represent the whole oil and gas industries. ...
doi:10.1504/ijaudit.2017.086747
fatcat:j3uqhfqkabcjvgrlzpfd35q3dy
Probabilistic Community and Role Model for Social Networks
2015
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15
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Numerous models have been proposed for modeling social networks to explore their structure or to address application problems, such as community detection and behavior prediction. ...
In this paper, we propose a unified probabilistic framework, the Community Role Model (CRM), to model a social network. ...
of structural hole spanner [29] . ...
doi:10.1145/2783258.2783274
dblp:conf/kdd/HanT15
fatcat:wvqpsfzmgva35mdydjv424zvhu
Identification of Compromised Nodes in MANETs using Machine Learning Technique
2019
International Journal of Computer Network and Information Security
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To achieve this, we conducted experiments using logistic regression (LR) and a support vector machine (SVM) to choose the best predictive model utilizing the Iris data set. ...
Mobile ad hoc networks (MANETs) are faced with various security challenges emanating from malicious attacks. ...
The dependent variable are the values to be predicted. They include the targets (y i ) of MANET data in which class's value depends on the metric (x i ). ...
doi:10.5815/ijcnis.2019.01.01
fatcat:ymj2dtkaejdlndxdxjeubjuuky
Downsizing and Structural Holes
1998
Communication Research
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Prominence is one of the most frequently used network metrics (Monge & Eisenberg, 1987) . ...
In addition, the individual relationships of structural hole items and the structural hole index were compared to the dependent variables to assess if the combined index demonstrated greater predictive ...
doi:10.1177/009365098025001002
fatcat:qhwhhfpmpjeifdol7jvufi6jni
Deep Neural Network Inverse Design of Integrated Nanophotonic Devices
[article]
2018
arXiv
pre-print
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Here we use deep learning to predict optical response of artificially engineered nanophotonic devices. ...
In addition to predicting forward approximation of transmission response for any given topology, this approach allows us to inversely approximate designs for a targeted optical response. ...
Discussion NNs can be used to take device structure data (shape, depth, and permittivity) to predict the optical response of the nanostructure (forward network). ...
arXiv:1809.03555v1
fatcat:mit74oz3y5ajzmplphhqinzzza
A Comparative Study of Target Tracking Approaches in Wireless Sensor Networks
2016
Journal of Sensors
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We then analyze them according to several metrics. We also discuss some of the challenges that influence the performance of tracking schemes. ...
Wireless sensor networks have been the subject of intense research in recent years. Sensor nodes are used in wide range of applications such as security, military, and environmental monitoring. ...
As shown in Figure 2 , there are six metrics: network structure, prediction-based mechanisms, type of chased object, type of sensor, number of targets, and recovery strategies. 3.1. ...
doi:10.1155/2016/3270659
fatcat:g4xz4dizx5eytm74fz5emt4fbq
Deep Neural Network Inverse Design of Integrated Photonic Power Splitters
2019
Scientific Reports
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Here we use deep learning to predict optical response of artificially engineered nanophotonic devices. ...
It has received some attention in optical community and there has been several recent work on reverse modeling for design of nano-structured optical components using DNN 19-25 , as well as hardware implementation ...
Discussion NNs can be used to take device structure data (shape, depth, and permittivity) to predict the optical response of the nanostructure (forward network). ...
doi:10.1038/s41598-018-37952-2
fatcat:mkzcoip5xzhhjf4mcddcclwmsa
Relating Wikipedia article quality to edit behavior and link structure
2020
Applied Network Science
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Additionally, we build a network of internal Wikipedia hyperlinks between articles. Using this data, we compute parsimonious metrics to quantify editing and linking behavior. ...
With our network analysis we find evidence indicating that controversial and edit war articles frequently span structural holes in the Wikipedia network. ...
subgroups due to their occupation of structural holes in the Wikipedia network. ...
doi:10.1007/s41109-020-00305-y
fatcat:2unnvgtgsbg3fgof6zpdjst54y
Developer social networks in software engineering: construction, analysis, and applications
2014
Science China Information Sciences
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The recorded information can be employed to construct Developer Social Networks (DSNs) for facilitating tasks in software engineering. ...
During the collaboration, a lot of new information related to software development, including developers' communication and coordination, can be recorded in software repositories. ...
[77] use a collaboration network derived from bug report repositories of Mozilla Firefox, to predict the risk and vulnerability in organization structures. Amrit et al. ...
doi:10.1007/s11432-014-5221-6
fatcat:ulahmalivrbcnhkrrlspogejdq
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