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Developer(s) | Social Media Research Foundation |
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Initial release | July 2008 [1] |
Stable release | 1.0.1.238 / 8 April 2013 |
Written in | C#, .NET Framework |
Operating system | Windows |
Size | 7.8 MB |
Available in | English |
Type | Data analysis, Data visualization |
License | Microsoft Public License |
Website | nodexlgraphgallery |
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NodeXL is a network analysis and visualization software package for Microsoft Excel 2007/2010/2013/2016. [2] [3] The package is similar to other network visualization tools such as Pajek, UCINet, and Gephi. [4] It is widely applied in ring, mapping of vertex and edge, and customizable visual attributes and tags. NodeXL enables researchers to undertake social network analysis work metrics such as centrality, degree, and clustering, as well as monitor relational data and describe the overall relational network structure. When applied to Twitter data analysis, it showed the total network of all users participating in public discussion and its internal structure through data mining. It allows social Network analysis (SNA) to emphasize the relationships rather than the isolated individuals or organizations, allowing interested parties to investigate the two-way dialogue between organizations and the public. SNA also provides a flexible measurement system and parameter selection to confirm the influential nodes in the network, such as in-degree and out-degree centrality. [5] The software contains network visualization, social network analysis features, access to social media network data importers, advanced network metrics, and automation.
NodeXL is a set of prebuilt class libraries using a custom Windows Presentation Foundation control. [6] Additional .NET assemblies can be developed as "plug-ins" to import data from outside data providers. Currently-implemented data providers for NodeXL include YouTube, Twitter, Wikipedia (the MediaWiki understructure), web hyperlinks, Microsoft Exchange Server. [7]
NodeXL is a collaborative effort of a number of individuals from different universities and other organizations forming the NodeXL Team. Notable contributors include: [8]
Microsoft Research established a NodeXL research project on November 20, 2008. [9]
NodeXL is intended for users with little or no programming experience to allow them to collect, analyze, and visualize a variety of networks. [10] NodeXL integrates into Microsoft Excel 2007, 2010, 2013, 2016, 2019 and 365 and opens as a workbook with a variety of worksheets containing the elements of a graph structure such as edges and nodes. NodeXL can also import a variety of graph formats such as edgelists, adjacency matrices, GraphML, UCINet .dl, and Pajek .net.
NodeXL Pro imports UCINet and GraphML files, as well as Excel spreadsheets containing edge lists or adjacency matrices, into NodeXL workbooks. NodeXL Pro also allows for the quick collection of social media data via a set of import tools which can collect network data from e-mail, Twitter, YouTube, and Flickr. NodeXL asks for the user's permission before collecting any personal data and focuses on the collection of publicly available data, such as Twitter statuses and follows relationships for users who have made their accounts public. These features allow NodeXL users to instantly get working on relevant social media data and integrate aspects of social media data collection and analysis into a single tool.
NodeXL workbooks contain four worksheets: Edges, Vertices, Groups, and Overall Metrics. The relevant data about entities in the graph and relationships between them are located in the appropriate worksheet in row format. For example, the edges worksheet contains a minimum of two columns, and each row has a minimum of two elements corresponding to the two vertices that make up an edge in the graph. Graph metrics and edge and vertex visual properties appear as additional columns in the respective worksheets. This representation allows the user to leverage the Excel spreadsheet to quickly edit existing node properties and to generate new ones, for instance by applying Excel formulas to existing columns.
NodeXL Pro contains a library of commonly used graph metrics: centrality, clustering coefficient, and diameter. NodeXL differentiates between directed and undirected networks. NodeXL Pro implements a variety of community detection algorithms to allow the user to automatically discover clusters in their social networks.
NodeXL generates an interactive canvas for visualizing graphs. The project allows users to pick from several well-known Force-directed graph drawing layout algorithms such as Fruchterman-Reingold and Harel-Koren. NodeXL allows the user to multi-select, drag and drop nodes on the canvas and to manually edit their visual properties (size, color, and opacity). In addition, NodeXL enables users to map the visual properties of nodes and edges to metrics it calculates, and in general to any column in the edges and vertices worksheet.
NodeXL has been used by news outlets such as Foreign Policy to visualize the structure of conversations about political topics as well as by organizations like the World Bank to analyze voting data. [11] [12] [13] NodeXL has been used as an analytical tool in dozens [n 1] of research papers in the social, information, and computer sciences, as well as the focus of research in human–computer interaction, data mining, and data visualization. [15] [16] [17] [18]
Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS. It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA). Excel forms part of the Microsoft 365 suite of software.
Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes and the ties, edges, or links that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, meme spread, information circulation, friendship and acquaintance networks, peer learner networks, business networks, knowledge networks, difficult working relationships, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through sociograms in which nodes are represented as points and ties are represented as lines. These visualizations provide a means of qualitatively assessing networks by varying the visual representation of their nodes and edges to reflect attributes of interest.
Graph drawing is an area of mathematics and computer science combining methods from geometric graph theory and information visualization to derive two-dimensional depictions of graphs arising from applications such as social network analysis, cartography, linguistics, and bioinformatics.
DOT is a graph description language, developed as a part of the Graphviz project. DOT graphs are typically stored as files with the .gv
or .dot
filename extension — .gv
is preferred, to avoid confusion with the .dot
extension used by versions of Microsoft Word before 2007. dot
is also the name of the main program to process DOT files in the Graphviz package.
Ben Shneiderman is an American computer scientist, a Distinguished University Professor in the University of Maryland Department of Computer Science, which is part of the University of Maryland College of Computer, Mathematical, and Natural Sciences at the University of Maryland, College Park, and the founding director (1983-2000) of the University of Maryland Human-Computer Interaction Lab. He conducted fundamental research in the field of human–computer interaction, developing new ideas, methods, and tools such as the direct manipulation interface, and his eight rules of design.
Graph Modeling Language (GML) is a hierarchical ASCII-based file format for describing graphs. It has been also named Graph Meta Language.
In business computer information systems, a dashboard is a type of graphical user interface which often provides at-a-glance views of key performance indicators (KPIs) relevant to a particular objective or business process. In other usage, "dashboard" is another name for "progress report" or "report" and considered a form of data visualization. In providing this overview, business owners can save time and improve their decision making by utilizing dashboards.
Dynamic network analysis (DNA) is an emergent scientific field that brings together traditional social network analysis (SNA), link analysis (LA), social simulation and multi-agent systems (MAS) within network science and network theory. Dynamic networks are a function of time to a set of graphs; for each time point there is a graph. This is akin to the definition of dynamical systems, in which the function is from time to an ambient space, where instead of ambient space time is translated to relationships between pairs of vertices.
Oracle Spatial and Graph, formerly Oracle Spatial, is a free option component of the Oracle Database. The spatial features in Oracle Spatial and Graph aid users in managing geographic and location-data in a native type within an Oracle database, potentially supporting a wide range of applications — from automated mapping, facilities management, and geographic information systems (AM/FM/GIS), to wireless location services and location-enabled e-business. The graph features in Oracle Spatial and Graph include Oracle Network Data Model (NDM) graphs used in traditional network applications in major transportation, telcos, utilities and energy organizations and RDF semantic graphs used in social networks and social interactions and in linking disparate data sets to address requirements from the research, health sciences, finance, media and intelligence communities.
Social data analysis is the data-driven analysis of how people interact in social contexts, often with data obtained from social networking services. The goal may be to simply understand human behavior or even to propagate a story of interest to the target audience. Techniques may involve understanding how data flows within a network, identifying influential nodes, or discovering trending topics.
JUNG is an open-source graph modeling and visualization framework written in Java, under the BSD license. The framework comes with a number of layout algorithms built in, as well as analysis algorithms such as graph clustering and metrics for node centrality.
Social network aggregation is the process of collecting content from multiple social network services into a unified presentation. Examples of social network aggregators include Hootsuite or FriendFeed, which may pull together information into a single location or help a user consolidate multiple social networking profiles into a single profile.
Social network analysis (SNA) software is software which facilitates quantitative or qualitative analysis of social networks, by describing features of a network either through numerical or visual representation.
A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key concept of the system is the graph. The graph relates the data items in the store to a collection of nodes and edges, the edges representing the relationships between the nodes. The relationships allow data in the store to be linked together directly and, in many cases, retrieved with one operation. Graph databases hold the relationships between data as a priority. Querying relationships is fast because they are perpetually stored in the database. Relationships can be intuitively visualized using graph databases, making them useful for heavily inter-connected data.
Gephi is an open-source network analysis and visualization software package written in Java on the NetBeans platform.
Meurs Challenger is an online graph visualization program, with data analysis and browsing.
Maltego is a link analysis software used for open-source intelligence, forensics and other investigations, originally developed by Paterva from Pretoria, South Africa. Maltego offers real-time data mining and information gathering, as well as the representation of this information on a node-based graph, making patterns and multiple order connections between said information easily identifiable. In 2019, the team of Maltego Technologies headquartered in Munich, Germany took over responsibility for all global customer-facing operations, and in 2023 complete technology development and management.
NetMiner is an application software for exploratory analysis and visualization of large network data based on SNA. It can be used for general research and teaching in social networks. This tool allows researchers to explore their network data visually and interactively, helps them to detect underlying patterns and structures of the network. It features data transformation, network analysis, statistics, visualization of network data, chart, and a programming language based on the Python script language. Also, it enables users to import unstructured text data(e.g. news, articles, tweets, etc.) and extract words and network from text data. In addition, NetMiner SNS Data Collector, an extension of NetMiner, can collect some social networking service(SNS) data with a few clicks.
The Science of Science (Sci2) Tool is a modular toolset specifically designed for the study of science. It supports the temporal, geospatial, topical, and network analysis and visualization of datasets at the micro (individual), meso (local), and macro (global) levels. Users of the tool can:
Andrej Mrvar is a Slovenian computer scientist and a professor at the University of Ljubljana. He is known for his work in network analysis, graph drawing, decision making, virtual reality, electronic timing and data processing of sports competitions.
...social network analysts have developed a number of software applications to analyze social network data. The most commonly used are: Pajek, UCINet, MultiNet, Siena, P*/ERGM, R, and NodeXL
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