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June

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

08JunMay 7, 2015 By Marc Smith

2014-IIeX-Atlanta
2014-IIeX-NA

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

Posted in 2014, All posts, Conference, Foundation, Industry, Measuring social media, Metrics, NodeXL, Presentation, Research, SMRF, SNA, Social Media, Social Media Research Foundation, Social network, Social Network Analysis, Social Theories and concepts, Talks, Technology, Visualization Tagged 2014, Atlanta, Conference, IIeX, June, Marc Smith, NodeXL, Talk 1 Comment

June 22, 2011: NodeXL at the NextWork Networks event in New York City

25JulMay 7, 2015 By Marc Smith

On June 22nd in New York City Wired Magazine and the Economist hosted a day of discussions and displays related to the theme of “Nextwork” hosted by Juniper Networks and located at the Tribeca Rooftop.

The Social Media Research Foundation displayed and printed  Nextwork Networks maps of the connections among the people who tweeted about the conference, the speakers, and their companies.

Visit the NextWork Network booth hosted by the Social Media Research Foundation to see a map of the connections among people who tweeted the term “NextWork“.  Networks are important data structures but the tools to access, analyze and visualize networks have been hard to use.  New tools now make networks as easy to handle as making a pie chart.  NodeXL, the free and open network overview, discovery and exploration add-in for the familiar Excel spreadsheet, makes creating network diagrams and gaining insights much simpler (see: http://nodexl.codeplex.com).  Using NodeXL, we have been collecting all the tweets that mention the NextWork event and building a network map of the ways those people connect to one another.  Not everyone is equally connected: some people occupy more strategic locations in the web of connections than others.   Find out who: request your own NodeXL social media network map for your Twitter account or the name of your company or brand (or your competitors) by dropping by the booth (or visit: http://www.smrfoundation.org/nextwork2011).

Here is an example, a map of the connections among the people who recently tweeted the name “Kevin Kelly”, one of the speakers at the event:

This is a map of the connections among the people who tweeted the term “Nextwork”:

Posted in All posts, Collective Action, Companies, Conference, Foundation, Industry, Measuring social media, Metrics, NodeXL, Research, SMRF, Social Interaction, Social Media Research Foundation, Social network, Social Network Analysis, Social Theories and concepts, Talks, Visualization Tagged 2011, 22, Analysis, Conference, Economist, June, Juniper, Marc Smith, network, New York, NextWork, NYC, SMRF, SNA, Social Media Research Foundation, Social network, Visualization, Wired

Bernie Hogan’s Facebook Network Map featured in Journal of Social Structure (JOSS) (Made with NodeXL)

08JulMay 7, 2015 By Marc Smith

The Journal of Social Structure has released its First Annual JoSS Visualization Symposium results and two of the images were generated with NodeXL.  One of the two is Bernie Hogan’s radial layout applied to representing Facebook Friend networks.

http://jossviz.wordpress.com/2010/06/23/friendwheel-layout-of-a-facebook-network/

The Journal of Social Structure (JoSS) is an electronic journal of the International Network for Social Network Analysis (INSNA).  Here is Bernie’s description of the graph.

This is a “pinwheel” diagram using the author’s Facebook personal network (captured July 15, 2009).

Nodes represent the author’s friends and links represent friendships among them. The author is not shown. Each ‘wing’ radiating outwards is a partition using a greedy community detection algorithm (Wakita and Tsurumi, 2007). Wings are manually labelled. Node ordering within each wing is based on degree. Node color and size is also based on degree. Nodes position is based on a polar coordinate system: each node is on an equal angle of n/360º with a radius being a log-scaled measure of betweenness. Higher values are closer to the center indicating a sort of cross-partition ‘gravity’.

This layout has several notable features:

– The angle of each wing is proportionate to its share of the network. Thus 25 percent of nodes go from 0 to 90º.

– Partitions are distinguished by their position rather than a node’s color or shape.

– The tail indicates the periphery of each partition. A wing with many tail nodes indicates many people who are only tied to other group members.

– Edges crossing the center show between-partition connections. Since nodes are sorted by degree it is easy to see if edges originate from the most highly connected nodes or the entire partition.



Bernie’s chapter on analyzing Facebook networks with NodeXL appears in the book: Analyzing Social Media Networks with NodeXL: Insights from a connected world.

Posted in All posts, Facebook, Industry, JCMC, JoSS, Journal, Network clusters and communities, NodeXL, Oxford, Papers, Research, Social Media, Social network, Social Network Analysis, Sociology, University, Visualization Tagged 2010, Industry, JOSS, June, network, Network clusters and communities, NodeXL, Papers, Politics, SMRF, SMRFoundation, SNA, Social Media Research Foundation, social network analysis, Technology, Visualization

July 22st, 2010 SNA event at Stanford: Network Analysis Made Easy: Using NodeXL To Map Social Media Networks

08JulMay 7, 2015 By Marc Smith

There is a Stanford Media X event on July 22nd, 2010 on new tools for SNA:

Network Analysis Made Easy:  Using NodeXL To Map Social Media Networks

http://mediax.stanford.edu/WSI/marc.html

Bring a laptop (running Windows and Office 2007 or 2010) to this workshop and you can be analyzing a social media network from systems like Twitter, flickr, YouTube and your own email by the end of the day.  If you can make a pie-chart in Excel, using the free and open NodeXL (http://nodexl.codeplex.com) you can now make a rich network graph from data extracted from social media systems and other common formats.  If you have a network, bring it, if not you can bring a suggested topic that we can map during the course of the day.

Even if you leave your laptop behind or have a Mac (sorry, no version is yet available for MacOS – unless you have a virtual machine with Windows and Office) this workshop will introduce the core concepts of network science with application to social networks in general and social media networks in particular. Applied to a range of topics and services, social media network maps can illuminate a variety of “publics” – populations who share a common interest and may share connections.  Maps of topics like “oil spill”, “global warming” and other issue and event related keywords can reveal the groups and factions that cluster around different concepts and terms.  Key contributors in these maps can be identified through the application of network measurements that capture various aspects of a  person’s location in a network graph.

Posted in All posts, Connected Action, Measuring social media, Media-X, Metrics, Network clusters and communities, Network data providers (spigots), Network metrics and measures, Network visualization layouts, NodeXL, Social Media, Social network, Social Network Analysis, Stanford, Talks, Visualization Tagged 2010, Analysis, Chart, graph, June, Media X, NodeXL, SNA, Social Media, Social network, Stanford

Paper: Tech Report at University of Maryland on EventGraphs

08JulMay 7, 2015 By Marc Smith

A new paper on visualizing social media has been released on the University of Maryland, Human Computer Interaction Laboratory tech report archive.  Co-authored by Derek Hansen,  myself, and Ben Shneiderman, the paper describes and visualizes the patterns of connections formed when people tweet about events like conferences and news stories.

EventGraphs_2010_HCIL_Tech_Report

http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2010-13

Hansen, D., Smith, M., Shneiderman, B.
EventGraphs: Charting Collections of Conference Connections
HCIL-2010-13

EventGraphs are social media network diagrams constructed from content selected by its association with time-bounded events, such as conferences. Many conferences now communicate a common “hashtag” or keyword to identify messages related to the event. EventGraphs help make sense of the collections of connections that form when people follow, reply or mention one another and a keyword. This paper defines EventGraphs, characterizes different types, and shows how the social media network analysis add-in NodeXL supports their creation and analysis. The paper also identifies the structural and conversational patterns to look for and highlight in EventGraphs and provides design ideas for their improvement.

Posted in All posts, Community, Connected Action, Maryland, Measuring social media, NodeXL, Papers, Research, Social Interaction, Social Media, Social network, Social Network Analysis, Sociology, Twitter, University, Visualization Tagged 2010, Analysis, Chart, EventGraph, graph, HCIL, June, Maryland, network, NodeXL, Report, SMRF, SMRFoundation, SNA, social, Social Media Research Foundation, Tech, UMD, University, Visualization

Mapping the connections among people who tweet #sunbelt

03JulMay 7, 2015 By Marc Smith

The International Sunbelt Social Network Conference is the official conference of the International Network for Social Network Analysis (INSNA).

This year’s INSNA “Sunbelt” conference is at the  Riva del Garda Fierecongressi, Trento, Italy!  Here is the 2010 INSNA Sunbelt Program.

This is the NodeXL map of connections among people who tweeted the hashtag used for the conference “#sunbelt”.

2010 - July - NodeXL - sunbelt - 2010-07-01

Having now seen several of these maps for other topics and events (see: http://www.flickr.com/photos/marc_smith/sets/72157622437066929/) this map can be placed in context.  It is a small group, but has a high density of connections.  It lacks isolates, the people who say the term but do not connect to others who say that term.  This means that this is a very “in-group” population: if you know to use the #sunbelt hashtag, you probably connect to someone else who uses the term.  It is a single major cluster of connected people, no obvious sub-graphs or clusters are visible.  Not everyone is central in the graph, and those who are have a prominent role in the network science community.  Here is the top ten list of #sunbelt mentioning twitter users ranked by betweeness centrality.

miriamnotten
barrywellman
memeticbrand
isidromj
drewconway
gephi
kristtina
danevans87
valdiskrebs
ciro

Posted in All posts, Conference, INSNA Sunbelt, Measuring social media, NodeXL, Social Media, Social network, Social Network Analysis, Twitter, Visualization Tagged 2010, Chart, Conference, graph, INSNA, July, June, Map, network, NodeXL, SMRF, SMRFoundation, SNA, social, Social Media Research Foundation, Sunbelt, Twitter, Visualization

Pierre De Vries Telco Industry Network Map featured in Journal of Social Structure (JOSS) (Made with NodeXL)

29JunMay 7, 2015 By Marc Smith

The Journal of Social Structure has released its First Annual JoSS Visualization Symposium results and two of the images were generated with NodeXL.  One of the two is “The Evolution of FCC Lobbying Coalitions” by Pierre de Vries, Research Fellow at the Economic Policy Research Center University of Washington, Seattle.

Pierre has been a deep student of telecommunications policy regulation in the United States for many years.  He has generated a remarkable network map built from the details of filings to the FCC over more than a decade.  These filings are made by companies when they agree or disagree with a proposed policy.  When two companies file in support (or opposition) to the same policy they create a tie between them.  The collection of these connections creates a complex network of coalitions and factions.

http://www.cmu.edu/joss/content/issues/2010jossviz/5_deVries.htm

“The graph is derived from meta-data associated with documents that are filed electronically whenever an organization interacts with the FCC, in accordance with the Administrative Procedures Act. Whenever a letter, comment or other document is filed, the filer provides information on the parties involved, number of pages, relevant proceedings, date, etc.”

…

“Once the data is cleaned up, an edge list is created in Excel by running another VBA macro. A graph is created from this list with NodeXL, a social network analysis and visualization add-in for Excel 2007. NodeXL’s Fruchterman-Reingold algorithm is used to prepare a preliminary layout; nodes are then moved by hand into visually intelligible positions, respecting the clusters suggested by NodeXL’s implementation of the Wakita-Tsurumi algorithm. Nodes are colored on the basis of eigenvector centrality. The degree of investment that organizations make in lobbying is measured by the total number of filings it made in this proceeding over the period of study, and reflected in the size of the node. This information is obtained by running another VBA macro against the underlying ECFS metadata, and then matching that to the vertices in the graph.”

Read more about this industry network at JoSS.

Posted in All posts, Industry, Network clusters and communities, NodeXL, Papers, Politics, Social Network Analysis, Technology, Visualization Tagged 2010, CMU, FCC, Industry, JOSS, Journal of Social Structure, June, network, Pierre De Vries, Regulatory network, SMRF, SMRFoundation, Social Media Research Foundation, Symposium, Telco, Visualization

New NodeXL Network Server (v1.0.1.126) – Frequently Asked Questions

14JunMay 7, 2015 By Marc Smith

NodeXL Network Server Frequently Asked Questions

The NodeXL team has released a new version (v.1.0.1.126) with better support for collecting data from social media network sources, starting with Twitter.  The NodeXL Network Server program now ships in every NodeXL installation.  Tony, the lead developer on the team, created the following FAQ to explain how to use the collector application.

This document describes how the NodeXL Network Server works.

  • What is the NodeXL Network Server?

It’s a Windows command-line program that downloads a network from Twitter and stores the network on disk in several file formats.  It can be run directly from a command line, but is typically scheduled to run on a periodic basis via the Task Scheduler that is built into Windows.

  • Where can the files be found?

The files are in NodeXL’s program folder.  To find out where the folder is, right-click the Microsoft NodeXL, Excel 2007 Template menu item in the Windows Start menu, then select Properties.  On 32-bit English computers, the folder is “C:\Program Files\Microsoft Research\Microsoft NodeXL Excel Template.”

  • Who are its intended users?

The Server is meant for use by people with moderate system administration skills.  It is not difficult to use, but it is not intended for the same audience as the NodeXL Excel Template, where ease of use is of high priority.

  • How do you run the Server from the Windows command line?

Like this:

NodeXLNetworkServer.exe NetworkConfiguration.xml

The program takes a single argument, which is the path to a configuration file that specifies which network should be downloaded and how the network should be saved to disk.  A particular configuration file might specify “Get the Twitter search network for people whose tweets contain ‘Sociology,’ add an edge for each ‘mentions’ relationship, limit to 100 people, include tweets, include statistics, and store the network as a GraphML file in the C:\NodeXLNetworks folder.”

The program immediately gets the requested network, saves it to disk, and exits.  On its own, it does not run on a periodic basis.

  • How do I create a configuration file?

You create a configuration file by copying a provided template file and editing the copy in Notepad.  The template file is named SampleNetworkConfiguration.xml and is stored in the same folder as the program.  The file is in XML format and the XML tags are clearly named and documented.

  • In what file formats can be the network be saved to disk?

You can save the network to either GraphML, which can be imported into a NodeXL workbook; directly to a NodeXL workbook; or both.

  • Do you typically run the program from the command line?

No.  Instead, you typically run it as a scheduled task via a built-in Windows program called Task Scheduler

Task Scheduler is a powerful utility that lets your run any program, including NodeXL Network Server, on a periodic basis.  You can, for example, tell Task Scheduler to run NodeXL Network Server using a particular network configuration file every twelve hours starting June 1, 2010 and ending June 30, 2010; or once a week starting now and continuing forever.  The scheduling options are endless.

  • Why not just include scheduling features in the NodeXL Network Server?

For two reasons.  First, Task Scheduler’s extensive scheduling options would be difficult to duplicate.  Second, if NodeXL Network Server had to download a network on a periodic basis, it would have to run as a Windows service, and Windows services are more complex to implement and to use than a simple command-line program.

  • How are the network files named?

Scheduling the NodeXL Network Server to run periodically can create any number of network files in the specified directory, so a file-naming scheme is needed.  The file name format is

{NetworkConfigFileName}_{Date}_{Time}.{Extension}.

So the above example, in which NetworkConfiguration.xml specifies that networks are to be saved as GraphML, might create a set of network files that look like this:

NetworkConfiguration_2010-06-01_02-00-00.graphml
NetworkConfiguration_2010-06-01_14-00-00. graphml
NetworkConfiguration_2010-06-02_02-00-00. graphml
…
  • What happens if the computer is not turned on at the scheduled time?

By default, the task won’t be performed until the next scheduled time when the computer is turned on.  However, if the computer is sleeping, you can tell Task Scheduler to wake it at the scheduled time to run the task.

  • What happens if the NodeXL Network Server encounters an error?

If the error prevents the network from being downloaded, the NodeXL Network Server creates an error file instead of a network file.  The file name starts with “Error” to make it easy to spot:

Error_NetworkConfiguration_2010-06-02_14-00-00.txt

The error file contains the details of what went wrong.

If one or more errors block part of the network but other parts of the network are successfully downloaded, then the NodeXL Network Server creates the network file containing the partial network, along with a text file that explains how many errors occurred.  The text file name starts with “PartialNetworkInfo” to make it easy to spot:

NetworkConfiguration_2010-06-02_14-00-00.Graphml
PartialNetworkInfo_NetworkConfiguration_Date.txt
  • What if I want to periodically download more than one network?

Simply schedule more than one task, each using a different network configuration file.  The tasks are independent of one another and can be scheduled to run at different times.

Posted in All posts, Metrics, Network data providers (spigots), NodeXL, Social Media, Social network, Twitter, User interface Tagged 2010, Chart, Data Collector, Desktop, Diagram, graph, GraphML, June, NodeXL, Server, SMRF, SMRFoundation, Social Media, Social Media Research Foundation, Twitter

Mapping #e2 OR #e2conf connections in Twitter with NodeXL

13JunMay 7, 2015 By Marc Smith

Enterprise 2.0

The Enterprise 2.0 conference is about to get underway in Boston. The event focuses on all the ways social media tools that are familiar on the consumer Internet are making their way behind the firewall in many enterprises and institutions. Why can’t you “friend” a colleague or “like” a spreadsheet or slide deck? Employees often come to their jobs expecting tools that resemble the social media tools with which they already spend much of their time.

Like many conferences, this one has a hashtag, actually two that I know of: #e2 and #e2conf. There is already a good deal of activity leading up to the event. Here is a map of connections among a group of people who mentioned either #e2 or #e2conf in the last few days.

2010 - June - NodeXL - #e20 All 2010-06-13_10-45-00

In this map there are 532 Vertices and 9,395 Unique Edges, creating 13 Connected Components, 11 of which had only a Single-Vertex, the largest component had 519 vertices which were interconnected 9,393 times.  The small number of isolated components indicates that this is a cohesive community of highly connected participants.  These people know and follow, reply and mention one another.  The Graph had a Density of 0.03 and the Maximum Geodesic Distance (Diameter) was 5 steps with an Average Geodesic Distance of 2.

Within this mass of connected users is a core group of highly “between” people, those who most broadly span connections within the population. These are one possible set of “influentials” within the Enterprise 2.0 community.

Here is a two screen view of the list of the top most between #e2 OR #e2conf mentioning twitter users along with the overview graph of their internal linkages.

2010 - June - NodeXL - #e20 Top Betweenness and Graph 2010-06-13_10-45-00

A closer look at the graph alone can reveal enough detail to read the names of these central participants.

2010 - June - NodeXL - #e20 Top Betweenness Graph 2010-06-13_10-45-00

This is a view of the list of authors sorted in Excel by their “Betweenness centrality” score, the measure of how much these people “bridge” across the network.

2010 - June - NodeXL - #e20 Top Betweenness 2010-06-13_10-45-00

An alternative view plots these contributors in an X/Y space based on their count of followers (along the x axis) and count of tweets (along the y axis).

The top 15 are:

dhinchcliffe
jowyang
rlavigne42
enterprise20
jumpersearch
marciamarcia
itsinsider
cmswatch
philcampos
rwang0
dankeldsen
lliu
juliancaparaz
lehawes
sameerpatel

2010 - June - NodeXL - #e20 All x followers y tweets 2010-06-13_10-45-00

Twitter users who mentioned #e2 or #e2conf on June 13, 2010 scaled by number of followers, x = log(followers), y = log(tweets).

There is a correlation between tweets and followers, but not everyone converts tweets to followers at the same rate. Below the diagonal are those who over convert tweets to followers, those above the diagonal under convert tweets to followers.

The book, Analyzing social media networks with NodeXL: Insights from a connected world, is forthcoming summer 2010 from Morgan Kaufmann and from Amazon.

Posted in All posts, Conference, Connected Action, Enterprise 2.0, Industry, Measuring social media, NodeXL, Social Media, Social network, Social Network Analysis, Twitter, Visualization Tagged #e2, #e2conf, 2010, Boston, Chart, Conference, Diagram, eventmap, June, Map, network, NodeXL, SMRF, SMRFoundation, SNA, Social Media Research Foundation, Social network, View, Visualization 1 Comment

Request a NodeXL Social Media Network Map

13JunAugust 25, 2015 By Marc Smith

Hello!  Social media network maps reveal the key people, groups, and topics discussed in a public conversation.
If you would like to request a custom social media network map made with NodeXL for the topic, hashtag, URL, or username of your choice complete the form below.  I will generate the maps as requests come in and email you a pointer to the results which I will post to the NodeXL Graph Gallery: See – https://nodexlgraphgallery.org/Pages/Default.aspx

Here is a sample map for the term “CustServ” (a discussion about providing better “customer service”):
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=14915

CustServ Twitter Connections for early January 2014

The visualization represents the connections among 1699 Twitter users over a 2-day, 21-hour, 48-minute period from Wednesday, 08 January 2014 at 02:53 UTC to Saturday, 11 January 2014 at 00:42 UTC.

In the sample map above for the term “CustServ” the visualization represents the connections among 1699 Twitter users over a 2-day, 21-hour, 48-minute period from Wednesday, 08 January 2014 at 02:53 UTC to Saturday, 11 January 2014 at 00:42 UTC.

The most central and possibly “influential” contributors to this discussion are:

@flavmartins
@gregsherry
@hyken
@billquiseng
@zendesk
@marshacollier
@helpscout
@adamtoporek
@cxalert
@virtualhold

Top URLs in the discussion were:

Continue reading →

Posted in All posts, Connected Action, Measuring social media, NodeXL, Social Media, Social network, Social Network Analysis, Twitter, Visualization Tagged 2010, Chart, Event, graph, June, Map, NodeXL, Request, SNA, Social network, Suggestion, Topic, Twitter, Visualization 39 Comments

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Transparency in Social Media
Sorin Adam Matei, Martha G. Russell, Elisa Bertino

CÓMO ENCONTRAR LOS HASHTAGS MÁS POTENTES: Para convertir LEADS a VENTAS (SEOHashtag nº 1) (Spanish Edition)

Apply NodeXL in espanol!

CÓMO ENCONTRAR LOS HASHTAGS MÁS POTENTES - Para convertir LEADS a VENTAS (SEOHashtag nº 1) (Spanish Edition)
By: Vivian Francos from #SEOHashtag Comparto algunas de las mejores formas de elegir los hashtags más poderosos y
que puedan generar tráfico a tus redes sociales para aprovechar el poder del
hashtag.
Si quieres aumentar tus interacciones, debes aprender a utilizar los hashtags como herramienta.

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