This weekend
we had HackU and while searching for ideas, I thought of why not make an app
which would visualize a complex network based on various input data,
but when I searched for similar apps found many softwares and apps already
available, and thus listed few of them:
Why Network Analysis tools required ?
Network
analysis tools allow researchers to investigate representations of networks of
different size - from small (e.g. families, project teams) to very large (e.g.
the Internet, disease transmission). The various tools provide mathematical and
statistical routines that can be applied to the network model.
Visual
representations of social networks are important to understand network data and
convey the result of the analysis. And thus these tools are used to identify,
represent, analyze, visualize, or simulate nodes (e.g. agents, organizations,
or knowledge) and edges (relationships) from various types of input data
(relational and non-relational), including mathematical models of social
networks
There are various Network Analysis tools
available for specific as well as generic purposes, few are mentioned here :
SocNetV (Social Networks Visualizer) is
an open-source graphical application, developed in C++ language and the
cross-platform Qt toolkit. The user interface is friendly and simple, allowing
the researcher to draw social networks or plain graphs by clicking on a canvas.
SocNetV computes basic network properties (i.e. density, diameter, shortest
path lengths), as well as more advanced statistics, such as centralities (i.e.
closeness, betweeness, graph), clustering coefficient, etc. Various layout
algorithms are supported. For instance, nodes can be automatically positioned
on circles or levels according to their betweeness centralities. Random
networks and small world creation is also supported. SocNetV can handle any
number of nodes, although with a speed penalty when nodes are more than 3000 or
the graph is quite dense (many edges).
Financial Network Analyzer (FNA) is an application for the statistical analysis of financial networks using methods developed in network science and social network analysis. It differentiates from other tools in that it builds networks from message (payments, trades, etc.) data and that it is geared towards the analysis of network times series.
igraph is a C library for the analysis
of large networks. It includes fast implementations for classic graph theory
problems and recent network analysis methods like community structure search,
cohesive blocking, structural holes, dyad and triad census and motif count
estimation. Higher level interfaces are available for R, Python and Ruby.
Text mining
tool that supports the extraction of relational data from texts. Distills three
types of information: content analysis, semantic networks, ontologically coded
networks. In order to do this, a variety of Natural Language Processing/
Information Extraction routines is provided (e.g. Stemming, Parts of Speech
Tagging, Named-Entity Recognition, usage of user-defined ontologies, reduction
and normalization, Anaphora Resolution, email data analysis, feature
identification, entropy computation, reading and writing from and to default or
user-specified database).
CFinder is a software for finding and
visualizing overlapping dense communities in networks, based on the clique
percolation method. It enables customizable visualization and allows easy
strolling over the found communities. The package contains a command line
version of the program as well, suitable for scripting.
Commetrix is a Software Framework and
Tool for Dynamic Network Analysis and Visualization. It provides easy
exploratory access to network graphs and has been applied to study co-authorship,
Instant Messaging, manual SNA surveys, e-mail, newsgroups, etc. Each node and
each linking event can have properties, e.g. types of messages or rank of
nodes, but also types, topics, or time stamps. This allows animations of
network growth, structural change, and topic diffusion.
iPoint monitors and analyzes Consumer
Generated Media, the full privacy of the author is maintained and its reporting
dashboard reads from iMediaStreams web services. The analysis is easily viewed
and managed from the worldwide, to the state, to the hyper local neighborhood
level. It is this aggregation of news and topics, overlaid with sentiment and
demographics, which provides a unique research tool into the areas that are
uppermost on peoples minds.
Java Universal Network/Graph (JUNG)
Framework is a Java API and library that provides a common and extensible
language for the modeling, analysis, and visualization of relational data. It
supports a variety of graph types (including hypergraphs), supports graph
elements of any type and with any properties, enables customizable
visualizations, and includes algorithms from graph theory, data mining, and
social network analysis (e.g., clustering, decomposition, optimization, random
graph generation, statistical analysis, distances, flows, and centrality
(PageRank, HITS, etc.)). It has been used to analyze networks in excess of 1
million nodes (although visualizations are currently more limited), and is
limited only by the amount of memory allocated to Java.
NodeXL is a free and open Excel 2007
Add-in and C#/.Net library for network analysis and visualization. It
integrates into Excel 2007 and 2010 and adds directed graph as a chart type to
the spreadsheet and calculates a core set of network metrics and scores.
Supports extracting email, Twitter, YouTube and flickr social networks.
Accepts edge lists and matrix representations of graphs. Allows for easy
manipulation and filtering of underlying data in spreadsheet format. Multiple
network visualization layouts. Reads and writes UCINet and GraphML files.
UrlNet is a Python class library for
generating networks based on Internet linkages. In the simplest case, UrlNet
creates a tree by harvesting the outlink URLs from the page referenced by a
root URL (level zero); retrieving each of those pages (level 1), harvesting
their outlink URLs; retrieving those pages (level 2), harvesting their outlink
URLs; et cetera to a caller-specified depth. UrlNet can also create
"forests", the union of multiple tree networks. Specialized classes
are provided for generation of networks from search engine result sets (6
search engines are currently supported). UrlNet can also utilize URL-based Web
Service APIs to generate networks. Current examples include Technorati's Cosmos
API and three types of networks utilizing APIs provided by the National Center
for Biological Information (NCBI) .
My favorite is the NodeXL as its easy to use and easy to integrate.
Cytoscape is an open source
bioinformatics software platform for visualizing molecular interaction networks
and biological pathways and integrating these networks with annotations, gene
expression profiles and other state data.
Although Cytoscape was originally designed for biological research, now
it is a general platform for complex network analysis and visualization. Cytoscape core distribution provides a basic
set of features for data integration and visualization. Additional features are available as
plugins.
NetEvo Framework C-Based Development
Kit (Cross platform) is a tool to study
the behavior of complex systems, it provides two main functions, simulation and
evolution of dynamical networks. To make use of these features, end-users must
provide the following to customize the framework for the problem of interest:
Set of
component dynamics for nodes and edges,
An initial
topology, unless the network can grow,
The evolutionary
process that searches for improved system configurations,
The
performance measure Q to guide evolution.
My favorite is the NodeXL as its easy to use and easy to integrate.
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