June 18th, 2014: IIeX-NA: Atlanta, Georgia

08JunMay 7, 2015 By Marc Smith

I will speak on June 18th at the IIeX-NA 2014 event in Atlanta, Georgia. The Insight Innovation Exchange conference focuses on advances in market research.

My talk is about the ways social network analysis can reveal important patterns in social media.

CHARTING COLLECTIONS OF CONNECTIONS IN SOCIAL MEDIA:

CREATING MAPS AND MEASURES WITH NODEXL

Susan Griffin (Chair), Marc Smith

lennyism OR insightnovation OR #IIeX Twitter NodeXL SNA Map and Report for Monday, 09 June 2014

The graph represents a network of 611 Twitter users whose tweets in the requested date range contained “lennyism OR insightnovation OR #IIeX”, or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 09 June 2014 at 00:24 UTC.

The requested date range was from Tuesday, 01 April 2014 at 00:00 UTC through Sunday, 08 June 2014 at 23:59 UTC.

The tweets in the network were tweeted over the 67-day, 4-hour, 35-minute period from Tuesday, 01 April 2014 at 00:26 UTC to Saturday, 07 June 2014 at 05:01 UTC.

There is an edge for each “replies-to” relationship in a tweet, an edge for each “mentions” relationship in a tweet, and a self-loop edge for each tweet that is not a “replies-to” or “mentions”.

The graph is directed.

The graph’s vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

The edge colors are based on edge weight values. The edge widths are based on edge weight values. The edge opacities are based on edge weight values. The vertex sizes are based on followers values. The vertex opacities are based on followers values.

Top 10 Vertices, Ranked by Betweenness Centrality:
@lennyism
@insightnovation
@beyondverbal
@socialdecode
@rebmannresearch
@danielfalcon
@lrwonline
@rafacespedes
@fearlesscomp
@eyeonmedialatam

Top URLs in Tweet in Entire Graph:
http://www.iiex-na.org
http://www.iiex-na.org/
http://www.iiex-na.org/sponsors/
https://events.bizzabo.com/iiexlatam2014/welcome
http://chile.feebbo.com/feebboch/surveys/anon/participate/3143
http://www.iicompetition.org/idea/view/312
http://www.iiex-latam.org/
http://www.iicompetition.org/idea/view/321
http://www.bloomberg.com/video/the-naked-brand-the-future-of-marketing-wTo1reeNTNugBjR1Qj~gnA.html
http://commun.it

June 27-29 2014: Networks in the Global World 2014, St Petersburg, Russia

08JunMay 7, 2015 By Marc Smith

NetGloW ’14: Bridging Theory and Method: American, European, and Russian Studies

June 27-29, St Petersburg, Russia

I will remotely participate in the conference “Networks in the Global World 2014. Bridging Theory and Methods: American, European and Russian Studies” taking place in St Petersburg, Russia, June 27-29 2014. The 2 day, single-track conference will also have pre-conference workshops including a day devoted to using the NodeXL social media network analysis application. The primary organizing institution and host is the Centre for German and European Studies, Bielefeld University and the St Petersburg State University.

This will be the 2nd Networks in the Global World conference (for information on the 1st one held in 2012 see http://www.ngw.spbu.ru). This conference series brings together researchers exploring cutting edge networks research from around the globe. In 2014 the focus is on linking theory and methods that integrate information, communication, semantic and cultural networks.

The primary goal of the NetGloW conference series is to bring together networks researchers from around the globe, to unite the efforts of various scientific disciplines in response to the key challenges faced by network studies today, and to exchange local research results – thus allowing an analysis of global processes. It is also crucial for us to support junior researchers’ orientation in the complex landscape of network science, and to encourage applications of network analysis by practitioners.

The idea of the 2014 event is to discuss the key current issues and problems of linking theoretical and methodological developments in network analysis.

The structure of the conference: June 27^th – workshops and seminar for practitioners; June 28^th & 29^th – presentations.

Confirmed invited speakers:

Jana Diesner, University of Illinois at Urbana-Champaign, USA
Loet Leydesdorff, University of Amsterdam, Netherlands
Tom Valente, University of Southern California, USA
Dimitris Christopoulos, MODUL University Vienna, Austria
Mario Diani, University of Trento, Italy
Peter Groenewegen, VU University Amsterdam, Netherlands
Wouter de Nooy, University of Amsterdam, Netherlands
Johanne Saint-Charles, University of Quebec at Montreal, Canada
Marc Smith, Connected Action Consulting Group, USA

The sessions of the conference will include the following:

Networks in Science, Technology, and Innovation: Traditional Approaches and Operationalization of New Theories
Words and Networks
Network Perspectives on Knowledge, Communication and Culture
Making Sense of Big Network Data: Testing Hypotheses on New Data
Social Movements and Collective Action as the Network Phenomena
Network Analysis of Political and Policy-making Domains

The conference will host workshops on the following network analysis software: ConText, Pajek, NodeXL, UCINet, RSiena.

The conference will include seminar Network analysis: How can it be used by globally operating practitioners?

Host: Center for German and European Studies (St. Petersburg State University – Bielefeld University).

Working language: English.

Abstracts (200 words) will be published as a part of conference programme. Full papers (2500 words) should be submitted prior to the event. Selected full papers will be published in peer-reviewed journal(s).

Free accommodation will be provided for MA and PhD students who submitted the best abstracts.

Fee: Participation in the conference is free of charge.

Further information about the conference and registration form can be found at www.ngw.spbu.ru or requested via e-mail: netglow@spbu.ru.

Book: Ways of Knowing in HCI (Kellogg and Olson, editors) Chapter on SNA and HCI

08JunMay 7, 2015 By Marc Smith

A new book edited by Wendy Kellogg and Judy Olson is now available. Ways of Knowing in HCI is a collection of chapters on the subject of methods and theories that frame Human Computer Interaction studies.

I co-authored a chapter in the book with Professor Derek Hansen from Brigham Young University on the role social network analysis can play in Human Computer Interaction.

: A social network consisting of Twitter users (nodes) who have Tweeted the word “global warming” connected to one another based on Follow, Reply, or Mention relationships (edges). Nodes are assigned different colors based on clusters. Hubs with many followers are indicated by size.

The chapter outline:

Introduction

A Brief History of Social Network Analysis

Social Network Analysis and Human-Computer Interaction

Goals of Social Network Analysis for HCI Researchers and Practitioners

1) Inform the design and implementation of new CSCW systems
2) Understand and improve current CSCW systems
3) Evaluate impact of CSCW system on social relationships
4) Design novel CSCW systems and features using SNA methods
5) Answer fundamental social science questions

Social Network Analysis Questions

Questions about Individual Social Actors
Questions about Overall Network Structure
Questions about Network Dynamics and Flows

Performing Social Network Analysis

Identify Goals & Research Questions
Collect Data
Sources of Network Data
Types of Social Networks
Representing Network Data

Three ways of representing network data

How to Analyze and Visualize Data
Network Analysis Tools
Commonly Used Network Analysis and Visualization Tools

Node-Specific Metrics: Focusing on the Trees

Common Centrality Metrics

Aggregate Network Metrics: Focusing on the Forest

Common Aggregate Network Metrics

Network Clusters & Motifs: Focusing on the Thickets

Network Dynamics and Information Flow

What Constitutes Good Work

References

NEW: NodeXL updates Twitter user and list importer

06JunMay 7, 2015 By Marc Smith

NodeXL has new updates to its importers for Twitter users and lists.

We have released an updated version of NodeXL that simplifies and merges the previously separate User and List importers.

The new, streamlined importer treats an individual user as a list of one.

Lists can be defined by pointing to an existing Twitter List or simply entering a list of delimited user names into the text box.

The updated importer now collects many more tweets per person and parses these messages to generate reply and mention edges.

You can now define a group of Twitter users and find out how much they reply and mention one another.

You can even pull in the followers of each person, to see if they reply or mention people they also follow.

But ever since June 11, 2013, Twitter has made access to the “follows” edge data very difficult (its just very slow). Designed and implemented prior to the update that restricted access to the follower network, the original NodeXL Twitter list importers relied mostly on queries that are now impractically slow for all but the smallest lists of users who have small collections of followers.

The update to these User and List importer is partially an adaptation to these changes. The importer shifts away from the follower network to focus on the communication interaction data in the content of Tweets. Since Twitter offers more generous access to Tweets than to information about who follows who, we are obliged to make better use of what they do offer.

The results are insightful! Here is a map of the connections among the members of the United States Congress.

VIDEO: SNA for fundraising and development webinar hosted by the Prospect Research Institute

05JunMay 7, 2015 By Marc Smith

I participated in a webinar hosted by the Prospect Research Institute. We discussed the ways that NodeXL can simplify the task of collecting social media and social network data. The tool generates easy to understand reports that highlight insights into connected structures.

The slides associated with the talk can be found here:

2014 TheNextWeb-Mapping connections with NodeXL from Marc Smith

Analyzing Social Media Networks with NodeXL: Insights from a Connected World

May 15, 2014: Keynote at Sam and Irene Black School of Business at Penn State University

07MayMay 7, 2015 By Marc Smith

I will speak at the Sam and Irene Black School of Business at Penn State University on Thursday, May 15, 2014.

I will talk about the themes Thinking across Boundaries, Learning by Doing, and Innovating through Collaboration in the context of the work of the Social Media Research Foundation to deliver an end-user friendly, free and open tool for social media network analysis.

The NodeXL project from the Social Media Research Foundation has crossed many boundaries, notably bridging the divide between the social sciences and the computer sciences.

We have learned a great deal as the NodeXL development team has released hundreds of updates to the application, guided by the feedback of our growing user community.

The Social Media Research Foundation team has innovated at multiple levels: organizationally we are a modern, virtual, distributed group of collaborators. Technically, we have focused our project on ease of use and automation rather than scale and sophistication, our users are not programmers. We have implemented many innovative network analysis and visualization techniques because we have been driven by a need to serve a diverse user population. The contributors to the project are themselves from a diverse range of disciplinary backgrounds, making it easier to shape the tool for the broadest audience.

Which social media network type is your topic? Which did you want it to be?

15AprMay 7, 2015 By Marc Smith

There are at least six different types of social media network structures present in systems like Twitter and other services in which people are able to reply to one another.

Each of the six patterns is generated by the behavior of the individuals in the population.

In many cases the pattern you are is not the pattern you want to be.

This table describes each of the six patterns in terms of the difference between that pattern and the other five patterns.

Go down the rows until you find the pattern that most closely matches the network you currently have. Then work across the columns until you find the pattern that you want to become.

At the intersection is a color and a few ways to change and measure the transition from where you are to where you want to be.

A red square indicates an undesirable transition (who wants to become a divided discussion?). A yellow square is a low probability and difficult transition (it is hard to go from divided to unified). A blue square is a challenge but possible while a green square is a fairly easy transition to make.

Using this guide, you can plan a strategy for your social media engagement.

This slide is part of a larger slide deck about using social media network analysis to guide engagement. Look for slide 71.

NodeXL Update v320 – Important news about upgrading your copy of NodeXL

14AprMay 7, 2015 By Marc Smith

The NodeXL team has just released a new version of the application.

Version 320 of NodeXL has some important changes.

Most important:
All existing users of NodeXL
*MUST*
* UNINSTALL *
all existing copies of the application from their systems
prior to installing this version.

Benefits: NodeXL will now provide automated updates. Everyday NodeXL will check for updated code and patch itself automatically.

This is the LAST update for NodeXL that will require user involvement. We will push new features out to users as they are available and they will just show up in user’s applications.

Some additional features of the latest update:

Imported Twitter networks now have an “in-reply-to tweet ID” column. This is a useful data element for building “paths” that capture how information flows through a network.
When you lay out each of the graph’s groups in its own box, you can now select how the boxes are laid out. Go to NodeXL>Graph>Layout>Layout Options in the Excel ribbon. (Thanks to Cody Dunne for this feature.)
The Check for Updates item has been removed from the Excel ribbon. NodeXL now automatically checks for updates once a day. Once this release is installed, NodeXL will automatically update itself when a new release is available. You will no longer have to manually download and install new releases. This release and those that follow will all be referred to as “NodeXL Excel Template 2014.” New releases will continue to have version numbers, but the numbers will be less important in light of the new auto-update feature.
If you use third-party graph data importers, such as the Social Network Importer for NodeXL, note that the folder where the importers are stored has changed. See “Using third-party graph data importers in NodeXL Excel Template 2014” at http://nodexl.codeplex.com/discussions/522826.
If you use third-party graph data importers, such as the Social Network Importer for NodeXL, note that the folder where the importers are stored must be specified in the NodeXL>Data>Import>Import Options dialog:
If you use the NodeXL Network Server, an advanced command-line program that downloads a network from Twitter and stores the network on disk in several file formats, note that the program is no longer a part of NodeXL Excel Template. See “Using the NodeXL Network Server command-line program with NodeXL Excel Template 2014” at http://nodexl.codeplex.com/discussions/522830.
When a Twitter network is imported, the hashtags in the “Hashtags in Tweet” (or “Hashtags in Latest Tweet”) column are now all in lower case. Previously, identical strings with different case letters would be counted differently. This is no longer the case and the result is that terms that had been divided are now unified. These terms will now have higher values and there will be more diversity in the top ten list.

Thanks for using NodeXL and stay tuned for additional updates!

Radio: OnTheMedia – Twitter Cartography – with Lee Rainie from Pew Internet

15MarMay 7, 2015 By Marc Smith

Lee Rainie, director of the Pew Internet Research Center was interviewed by Bob Garfield on OnTheMedia this week about the recently released report on mapping Twitter topic networks. The report found six distinct patterns of social media networks in Twitter: divided, unified, fragmented, clustered, and in and out hub and spoke patterns. They discuss the prospects for overcoming polarization in social media and the hopeful signs that many other forms of social network structures exist in addition to the divided network pattern.