Data Visualization in NodeXL Assignment Help

Introduction to Data Visualization in NodeXL Assignment Help at AssignmentHelp

“NodeXL is a free, open-source template for Microsoft® Excel® 2007 and 2010 that simplifies network graph exploration. A network edge list can be inserted in a worksheet, a button can be clicked, and a graph can be viewed with NodeXL, all in the familiar context of the Excel window.” WHO WILL NEED IT? Professionals interested in applying network analysis to business challenges Students learning social media network analysis

You can explore the presence or absence of reciprocal linkages and closed triads in your egocentric Twitter network using NodeXL. Because most egocentric networks are made up of a combination of strong and weak social links, combining reciprocal linkages and triads into a single number frequently leads to erroneous assumptions about your social circle. Visualizing your social network, on the other hand, might reveal information about your close versus distant links, as well as exchanges between close friends and acquaintances.

Overview

This research analyzes a Twitter dataset related to students' interests using NodeXL, a social network analysis tool. Each student will create their research questions and hypotheses for the project, collect their data, then analyze the data and answer their questions using the software.

Before utilizing the software, students will learn about network analysis, major network concepts (nodes, links, clusters, and so on), centrality and centrality measures (degree centrality, proximity centrality, betweenness centrality, eigenvector centrality), and network visualizations. These concepts will be applied to a Twitter network, with a focus on understanding influence and social capital on the internet. There will also be time focused on how to develop research questions and hypotheses that are relevant to this project.

Additional className times will be spent learning how to utilize the software and understand the data in a computer lab. Students are expected to spend time in the lab outside of className.

Finally, the project concludes with a short (3-5 page) research report in which students explain their findings in both text and network visualizations. Students must present their RQs and Hs, as well as “show” their data and provide educated interpretations about what the data indicated.

WHY IS IT APPROPRIATE AND EASY TO USE?

Provide an easy-to-use tool for nonprogrammers by building on the familiar spreadsheet paradigm.

A wide range of visual characteristics Includes powerful automated capabilities while allowing for manual control graphical design integrates metrics, statistical methodologies, and visualization: gets the benefit of all three approaches Supports work with small networks with a few thousand vertices.

The Twitter Users Network importer in NodeXL Pro

The NodeXL Pro Twitter Search Network importer can only access data from the previous 10 days, but the NodeXL Pro Twitter Users Network importer can get any user's most recent 3,200 tweets, including retweets and responses. As a result, depending on a user's tweet behavior, this data could last much longer than the 10-day limit.

In the box The Twitter Users with these identities, you can input any list of public Twitter handles.

If you check the box Import only the Twitter people I'm interested in, you'll only get edges between the users in the list, which we refer to as the internal network. If you leave the box unchecked, you'll get the entire network, including all retweeted, mentioned, and replied-to Twitter individuals.

Data Visualization in NodeXL Assignment Help By Online Tutoring and Guided Sessions from AssignmentHelp.Net

A {"Group"} in NodeXL is a group of vertices in a network that can be collected together. The following are some of the characteristics of groups:

The vertices in selected groups can be worked on as a set, and the groups can be collapsed or expanded. Network metrics can be generated for each group, and the groups can be visualized inside bounded boundaries.

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