Review of Meltwater Media Intelligence Software by Matthew J. Kushin

1. Public Relations Education
Association for Education in Journalism and Mass Communication
Journal of
JPRE
Volume 4, Issue 2, Fall 2018
A publication of the Public Relations Division of AEJMC
ISSN 2573-1742

2. Volume 4, Issue 2, Fall 2018
A publication of the Public Relations Division of AEJMC
ISSN 2573-1742
© Copyright 2018 AEJMC Public Relations Division
Journal of Public Relations Education
Editorial Staff
Emily S. Kinsky, West Texas A&M University, editor-in-chief
Tiffany Gallicano, University of North Carolina at Charlotte,
senior associate editor
Lucinda Austin, University of North Carolina at Chapel Hill,
associate editor
Chuck Lubbers, University of South Dakota, associate editor of reviews
Kathleen Stansberry, Elon University, web manager
Note from the Editor-in-Chief:
In this issue, you will find three research articles, all five of the top
AEJMC PR Division’s Great Ideas For Teaching presented in Washington,
D.C., and two reviews by Matt Kushin, which relate to one another on the
topic of teaching social media.
Volume 4, Issue 2 reflects an incredible amount of work done prior to
my editorship. The previous editor-in-chief, Chuck Lubbers, handled the
review assignments for each of the research articles for this issue prior to
me moving into this role on Jan. 1, 2018, and two of them were accepted
for publication under his tenure in 2017. The first acceptance letter I was
honored to send as the editor went to Drs. Brunner, Zarkin and Yates. A
special thanks to Chuck for his work with authors and reviewers to get us
ready for Volume 4.
Thank you to Tiffany, Lucinda, Chuck and Katie, who have invested
countless unpaid hours proofreading, editing and formatting this issue.
Without your service, this issue would not exist. Special thanks go to
Rebekah Grome, who also came to our aid with proofreading.

3. Table of Contents
Research Articles
1-20
21-50 What do Employers Want? What Should Faculty Teach? A
Content Analysis of Entry-Level Employment Ads in Public
Relations
Brigitta R. Brunner, Kim Zarkin, & Bradford L. Yates
51-86 Teaching Digital and Social Media Analytics: Exploring Best
Teaching Briefs
PRD GIFT Winners from AEJMC 2018
87-98 Building a Social Learning Flock: Using Twitter Chats to
Enhance Experiential Learning Across Universities
Amanda J. Weed, Karen Freberg, Emily S. Kinsky,
& Amber L. Hutchins
99-106 Diagnosing Health Campaigns: A Campaign Evaluation
Assignment
Laura E. Willis

4. Teaching Briefs (continued)
PRD GIFT Winners from AEJMC 2018
107-114 Teaching Trolling: Management and Strategy
Leslie Rasmussen
115-122 Sparking Creativity Through Purpose-Driven Storytelling
Chris Cooney
123-127 Looking in to see out: An Introspective Approach to Teaching
Ethics in PR
Regina Luttrell & Jamie Ward
Reviews
128-133 Social Media Campaigns: Strategies for Public Relations and
Marketing
Matthew J. Kushin
134-145 Meltwater Media Intelligence Software
Matthew J. Kushin

5. Meltwater Media Intelligence Software
Review by
Matthew J. Kushin, Shepherd University
Website: https://www.meltwater.com
Cost: Free with Meltwater University Program
Contact: Carol Ann Vance, Director of Talent Acquisition, Americas,
carolann@meltwater.com
Meltwater media intelligence software (https://www.meltwater.
com) is an online software suite that enables subscribers to conduct news
and social media monitoring, as well as build media lists and perform
media outreach (Business.com, 2018). Like many of its competitors, such
as Radian6 and Cision, Meltwater follows the software as a service (SaaS)
model. Users subscribe and log in via their web browser to access the
software package. Users do not need to download any files or software to
use the service. There is also an optional mobile app available in the App
Store and Google Play that enables users to access many of the service
features on their mobile device (“Meltwater Mobile,” n.d., 2018).
The software works by allowing users to search public social
media data from platforms such as Twitter, Instagram, YouTube, and
Facebook, as well as forums, blogs, comments, and product reviews
(Business.com, 2018). Similarly, the software enables users to search
articles from news databases. A search can be used to look back in time
to past social media posts or news articles. Once set up, a search will
collect social media posts or news articles going forward. According to the
Meltwater help center website, news searches go back to the start of 2009,
and social media searches go back a rolling 15 months (Apple, n.d.).
Since January 2017, Meltwater has offered a university program,
which enables faculty and students to get free access to the software to use
in the classroom for educational purposes. Carol Ann Vance oversees the
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university program at Meltwater. Software training was initially provided
through an optional introductory video call with the professor and class;
however, due to the scale of the university program, the company has
moved to a model of making training videos accessible. In addition, online
training is embedded into the help section of the software.
Overview of Meltwater
The Meltwater software is divided into functions via a navigation
menu on the left. The first part of this review focuses on functions related
to the news and social media search features. Following that, additional
supporting features are noted.
Search
Users set up searches for keywords or phrases and provide time
and date parameters. Searches can be for either news or for social media
content. As their titles suggest, news searches enable users to search a real-
time database of news articles across a growing list of more than 300,000
news sources (C. A. Vance, personal communication, May 23, 2018).
Multiple searches can be programmed to run concurrently. Social media
searches enable users to search a variety of social media platforms, as well
as forums, blogs, and product reviews.
A search can be set up by navigating to the “Search” menu item.
A user enters a keyword to begin a search. Once a search is initiated,
additional keywords can be entered. Further, after a few keywords are
entered, a list of related keywords is generated and suggested by the
software. The user has the option of including those keywords in the
search. Similar to searching on other platforms, keywords can take a
variety of forms, including but not limited to a word or phrase of interest;
the name of a person, organization, or entity; a hashtag; or a username.
Users have three options for the types of search they want: (1) all of
these keywords, (2) at least one of these keywords, or (3) none of these

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keywords (see Image 1). These options can be combined in a single
search. Users can also enter search terms using Boolean logic in the
advanced settings. Date parameters and source parameters can be set.
News source parameters include location, source type, reach percentile,
among others. Social media parameters include source type and language.
Image 1
Screenshot of Meltwater’s search tool
Image used with permission from Meltwater.
Once a search is set up or after an existing search is edited, the
user begins to see the results in real time. Searches default to a reverse-
chronological view, with the most recent post at the top. The results can be
sorted by a number of other dimensions, including reach, sentiment, and
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geolocation. Each item in the search results is organized into a “content
card,” which contains metadata appropriate to the type of search. For
example, for a news search, metadata information includes publication,
headline, byline, date and time of publication, reach, and sentiment score.
In each content card, the first few lines of text to a news post are shown, as
well as a photograph. Clicking on the article headline takes the user to the
original article in a new browser page. Similarly, users can sort metadata
in social media searches and access the original post by clicking on the
social media profile data associated with search results.
Dashboards
Dashboards are created from existing searches. They can be
accessed by navigating to the “Dashboards” menu item. Therefore, a user
must first set up a search for a topic of interest before creating a dashboard
for that topic. Dashboards are visual representations of data from a search,
and they are organized into interactive widgets (see Image 2). Widgets
are displayed as windows within a dashboard and, as the name suggests,
function to analyze and display information visually. There are a variety of
widgets, including but not limited to widgets that display share of voice,
potential reach, media exposure, sentiment, trending themes, top locations,
top sources, a heat map, and a Google Analytics widget. Each widget
can work with one or more of the following sources: news, social or RSS
feed. Each widget can be interacted with and customized individually,
enabling the user to modify the date range and the search source for that
widget. Further, the location and size of widgets can be changed within
a dashboard. As such, Dashboards serve as the key way to interact and
analyze data in Meltwater.
There are three default dashboards: monitor, benchmark, and
analyze. Additionally, users can set up custom dashboards by picking and
choosing the widgets of their choice. All dashboards can be customized by
adding and removing widgets from the settings in a dashboard. Multiple
dashboards can be programmed to run concurrently, and users can set up

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multiple dashboards for the same search. It is worth noting that data from
dashboards can be downloaded in CSV format for analysis in external
software, such as in Microsoft Excel.
Image 2
Screenshot of the Meltwater Dashboard
Image used with permission from Meltwater.
Influencers
The influencer tool enables students and professors to build
searches for influencers working at news outlets and to build media lists.
Users can search for influencers and their associated news source through
Meltwater, import a list of contacts from a CSV file, or create individual
influencers manually by entering their contact data.
To build a media list using the Meltwater search software, users
start a new search and select whether they are searching for “Contacts”
or “Sources.” Several filters enable users to focus their search on key
parameters, such as beats, source reach, geographic focus, language,
media channel, and others. Once a search is run, the user can select from
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the results to see detailed information about the reporter or media outlet
(see Image 3).
Image 3
Screenshot of Influencers Tool in Meltwater
Image used with permission from Meltwater.
Additional Features
In addition to the features above, Meltwater contains several
additional features.
Home
The “Home” menu item is a default view that a user sees when
logging into Meltwater.

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Inbox
The “Inbox” menu item is a place to organize RSS feeds and
searches that a user has programmed.
Tags
Tags are created by users in the “Tags” menu item. They can be
used to classify and thus organize content for easy access later. Articles or
social media posts can be tagged via the search results.
Outputs
The “Outputs” menu item enables users to output, or share,
search content from pre-programmed Meltwater searches to a third party
outside of the Meltwater platform. This may include internal parties such
as direct reports or external parties such as clients or website visitors.
In the classroom context, students could create outputs to share with the
professor or with class clients.
Outputs take one of two forms: 1) newsletters and 2) newsfeeds.
A newsletter allows a user to pull posts from a preprogrammed search
to send via email. The newsletter is organized by sections, which
contain user-selected posts from a search and which can contain
explanatory text that the user can add. Each section can contain data
from a separate preprogrammed search. Once set up, the newsletter can
then be emailed to an email list, which can be imported in CSV format.
The newsfeeds feature enables a user to create a feed of posts from a
single preprogrammed search. A website administrator could then use
the generated RSS or XML to produce a web feed to be hosted on an
organization’s website. These features are not likely to be used in the
learning environment.
PR Insights
This feature is not available through the university program. It
enables users to create custom reports of Meltwater data.
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Settings
The “Settings” menu item is where users manage their account
information and customize preferences. Importantly, the settings feature is
also where users can connect Instagram and Google Analytics to pull data
into Meltwater from those services.
Level of Expertise Required for Use
The user should have a working knowledge of social media, social
media analytics, and media relations. The interactive, visual nature of the
software is approachable but can be cumbersome. The available help tools
within the software provide resources, including step-by-step videos, for
professors to learn the software and teach it to students. But, learning to
use the software effectively requires a substantial time investment. Given
that the software can be accessed via a web browser or via the native
apps (Business.com, 2018), it can be readily accessed by professors and
students both on and off campus, irrespective of operating system.
My Experience with the Software
I integrated the Meltwater software in my undergraduate 300-level
social media course in fall 2017. To me, the power of the software is in
its ability to quickly pull historical data from a variety of sources. Unlike
other software that I have used, Meltwater does not require a user to set
up a search ahead of time to begin collecting data for future analysis. This
enabled my class a lot of flexibility in what we were able to search. With
other software, I have had to pre-program searches at the beginning of the
semester and wait several weeks to collect enough data to use for class
projects.
However, there were some hiccups and challenges with using the
software. I will discuss several below.
We began with a brief activity where students set up a few searches

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to monitor social media content related to a well-known health and beauty
brand and its competitors. The purpose of the activity was to familiarize
students with what the software was capable of monitoring on the social
media side. Here, we ran into a few issues where software usability
challenges and user inexperience conspired to create problems. First, when
setting up their searches, students struggled to get creative in generating
the search keywords. Beyond the brand names themselves, I tried to
encourage creativity. For example, I suggested using the brand’s social
media account handles and using various spellings of the brand names
(e.g., with and without an apostrophe in one case). Students also did
not tend to look at the search results to look for false positives. In some
cases, students needed to go back and add keywords to the “None of these
keywords” textbox to refine results. Altogether, students tried to rush this
important process.
Second, some students struggled to follow the instructions to
make the search a social search, accidentally setting up the search as
a news search instead. Students didn’t seem to understand how the
“news” and “social” searches differed, despite having taken the video
training provided in the software as well as my brief lecture in class.
Both the variations in keyword choice in search set up and the mistake of
creating a “news” search instead of a “social” search led to inconsistent
results between students when they analyzed their search result data in a
dashboard. Third, several students stumbled through understanding that
a dashboard was needed in addition to a search to see analytics. They
expressed that they felt that the search should auto-generate a dashboard.
Because there are several different types of dashboards, the differences for
which are not immediately clear, they grew frustrated and confused. These
students did not understand that the search serves to pull in the data, and
can be modified, and that the dashboard provides the output of the data via
the widgets. Fourth, when setting up additional widgets within an existing
dashboard, a user must select which search to pull the data from. Several
students selected the wrong search unknowingly, and were thus believing
they were seeing data for one brand when in fact they were seeing data for
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a different brand.
In ways such as those described above, students seemed to struggle
with grasping how to navigate and use the software. Those struggles led
students to believe they were reporting the correct data when in fact they
were not.
Turning now to the data the software provides, there are a few
limitations to be aware of.
First, be aware that the software is a monitoring tool and does not
provide access to analytics of social media accounts. My students also
completed a social media audit assignment and we were only able to use
some features of the Meltwater software. For example, we were unable to
find a way to use the software to explore analytics surrounding a specific
social media account (e.g., a Facebook page and its followers, or audience
demographics). This is likely because this information is not public.
Therefore, for certain assignments, additional tools or client access to
built-in analytics will be needed in the classroom beyond Meltwater.
Second, while the news media influencer tool is great for building
media lists, it was a bit challenging to help students identify social media
influencers via Meltwater. There are a few proxies which can be used to
try and triangulate a search for social media influencers. I had my students
sort searches by reach and by engagement. There is also a dashboard
widget for finding the top posters by volume, as well as a widget for share
of voice. However, a separate tool for identifying influencers in a social
conversation would be a wonderful addition.
Third, in my own experience, I found the widgets a bit
cumbersome to navigate. From a dashboard, one has to click into the
widget by clicking the blue arrow before a widget can be interacted with.
Interaction with the widgets feels a bit one-dimensional. When a data
point – such as a date – is clicked on in a widget, the software displays all
results pertaining to that data point. However, many widgets do not allow
further drilling down. For example, if the widget showed search volume
for a four-month period and I clicked on one day, the widget will not zoom
in on that day and show me a timeline of posts across the hours of that day.

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In this regard, I was not able to see what time of day search volume was at
its highest.
Upon completing our use of the software throughout the semester,
I asked students for verbal feedback about their experience. Some
expressed excitement and a sense of empowerment, others expressed
a sense that they learned a lot, and a few expressed a sense of being
overwhelmed or intimidated. A majority of students said that they wished
I had spent more time in class showing them how to use the software. I
recommend that professors planning to use the software in their classroom
offer ample in-class opportunities for students to learn to set up searches
properly and refine searches through keyword targeting. I also recommend
walking students through the dashboard setup a few times and checking
for understanding and task completion. Look for discrepancies between
students in their results, and help students to reverse engineer how
decisions they made in setting up their search led to those discrepancies.
Conclusion
The Meltwater media intelligence software provides a powerful
software suite for teaching students about news media monitoring, social
media monitoring, and analytics. Meltwater is also a powerful tool for
teaching students key media relations skills, namely identifying relevant
news outlets and reporters and building media lists.
By integrating the Meltwater software into classes in public
relations and social media through activities and assignments (see https://
www.slideshare.net/CarolAnnFunkhouser for examples), professors can
expose students to media intelligence software used by more than 25,000
organizations around the world (O’Malley Greenburg, 2017).
References
Apple, M. (n.d.). Meltwater content: How much data do we store?
Meltwater: Welcome to the help center. Retrieved from https://
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Editorial Record: Submitted to the associate editor of reviews on May 30, 2018. First
published online on August 17, 2018.
support.meltwater.com/hc/en-us/articles/115015823988-Meltwater-
Content-How-much-data-do-we-store-
Business.com. (2018, July 12). Meltwater review. Retrieved from https://
www.business.com/reviews/meltwater/
Meltwater mobile. (n.d.). App store. Retrieved from https://itunes.apple.
com/us/app/meltwater-mobile/id959583041?mt=8
Meltwater mobile. (2018, July 9). Google Play. Retrieved from https://
play.google.com/store/apps/details?id=com.meltwater.mobile
O’Malley Greenburg, Z. (2017, May 23). Google slayer: Meet Meltwater,
the company that conquered Google Alerts. Forbes. Retrieved from
https://www.forbes.com/sites/zackomalleygreenburg/2017/05/23/
google-slayer-meet-meltwater-the-company-that-conquered-
google-alerts/#221215216422