Tag Archives: social media class

What Happens When You Put Your Students In Charge of Your Department’s Social Media? (My Fall 2015 Social Media Class Project In Review)

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The new semester has started here at Shepherd University. There is a lot I have planned and am looking forward to. But first, I want to look back at my Comm 322 Social Media class from last fall, Fall 2015.

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Social Media Documentary Recommendation: Generation Like

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When I was in college, I remember watching “Merchants of Cool,” a PBS Frontline documentary chronicling the strategies marketers use to appeal to the elusive teenage demographic.

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My Fall 2014 Social Media Class Project In Review

shepherdcommunication-socialmedia
Typo! What happens when I Tweet from my phone while in a rush. 😛

In the last few posts, I’ve been writing about my Social Media class and the semester project we’ve been doing. To recap, students create a social media content strategy for our department’s social media (the details of the assignment are on the previous post). They then use this plan to create content for the department. They create content 3  times, each time they are creating content for a certain time period. The content is presented to the class and then goes through an editorial process (i.e.., I grade them and make any needed mods) if needed before being published.

With the semester winding down, I want to share some of the work the students have been doing!

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A Look at My Social Media Content Strategy Assignment

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Several weeks ago I mentioned that a big change in my Comm 322 Social Media class this semester (syllabus), is that students will be working to create the social media for our department’s Twitter, Instagram, and a brand new blog.

Continue reading A Look at My Social Media Content Strategy Assignment

Sentiment Analysis using Content Analysis Software: Project Assignment

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In the last two posts, I’ve been discussing the Yoshikoder sentiment analysis project in my Communication Research class here at Shepherd University.

My first post looked at the project in general. And the second, most recent post, looked at how to teach computer-assisted content analysis using the Yoshikoder computer-assisted content analysis software and the activities I provide my students to prepare them for the project.

I encourage you to check out those posts for background and set up! Ok, now on to sharing the assignment itself and providing a brief overview of it.

As I’ve stated elsewhere, the purpose of this assignment is to

1) give students a hands-on look under the hood of sentiment analysis – that is, to understand HOW it works and its flaws.

2) To teach students via hands=on experience about quantitative content analysis, particularly computer-assisted content analysis

3) To teach them how to conduct a computer-assisted content analysis using software (Yoshikoder)

So here’s the set up to the assignment (which you can see below). This hands-on learning project is based on a real brand and a realistic but made up scenario. I do this with both this assignment, and my first project in this class.  Specifically, I provide The Situation or Problem / Campaign goals and objectives (of an imaginary campaign that is ongoing or happened) / benchmarks / KPIs.

In this case, the situation had to do with a popular online retail brand and rising customer complains and dissatisfaction as the brand has grown beyond its core base of loyal customers in recent years.I’ve redacted the brand and the situation from the below assignment. But you can fill in your own.

I rely on Stacks (2011) model for writing the problem, goals, objectives.  While I provide the research objective(s) in my first project, in this project students must come up with the research objective(s) and RQ(s).

I then provide some benchmarks. In this scenario, at a certain point in time sentiment was strong (let’s say, 70% positive). And then after the hypothetical situation, it dropped (say, to 50%). The students have been recently introduced to the concepts of benchmarks and KPIs via a brief lecture, so this is their first experience with these concepts. They are given 1 KPI (let’s say 65% positive sentiment) against which to measure their success. Keep in mind that the situation assumes that a campaign already took place aimed at addressing decreased customer satisfaction and negative comments on Twitter addressed at the brand of choice. We are now seeking to assess whether this campaign that happened successfully increased sentiment towards the brand (at a deeper level, repaired relationships and the image of the brand among the online community).

There are other important considerations students must make:

1) Since we’ve discussed sentiment and its flaws, they need to think about the valence of sentiment (The AFINN dictionary scores terms from -5 to +5), and they need to research and understand how AFINN was designed and works (I provide some sources to get them started). If you’re not familiar with the AFINN dictionary, it was designed for sentiment analysis of microblogs.It is a free sentiment dictionary of terms you can download and use in Yoshikoder. 

For more details on the assignment, check out the assignment embedded below and the requirements for what must be turned in.

As I’ve noted in a previous post, this project isn’t perfect. But it is a fairly straightforward and accessible learning experience for students who are in their first semester of experiencing how research can be conducted. It covers a wide array of experiences and learning opportunities – from discussion of what sentiment is, to understanding its flaws, to understanding the flaws of quantitative content analysis, to learning to apply a number of key research terms, as well as providing exposure to how to write research reports. The project itself is bolstered by several lectures, it comes about 1/2 way through the semester, and takes several days in the classroom of hands on learning. Students of course finish the writing up outside of class. But we do the analysis all in class to ensure students are getting my help as the “guide on the side.”

My previous post covers some activities we do to build up to this assignment.

So that’s all for now! Please feel to use this assignment, to modify it, and improve it. If you do, come back and share how you have or how you would improve upon it and modify it in the comments below!

If you want to know more about my Communication Research class, please see this post which includes the syllabus.

Teaching Computer-Assisted Content Analysis with Yoshikoder

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Last blog post I discussed the second project in my applied research class, a sentiment analysis of Tweets using Yoshikoder – a free computer-assisted content analysis program from Harvard.

As promised, I want to share my assignment, and my handout for students that teaches them how to use Yoshikoder. Before we do the project, however, I do a brief in class activity to get students learning how to use Yoshikoder. So let’s start there for today’s post. And next post, I’ll share the assignment itself.

PART 1: THE SET UP

What I like to do, is present the problem to the students via the project assignment. Then, we go back and start learning what we’d need to do to solve the problem. So, after lecturing about what sentiment analysis is and why it is important, I get students introduced first to the idea of constructing a coding sheet for keywords by taking a list of keywords and adding them to categories.

First, we talk about the idea in class, and I show them some simple examples, like: If I wanted to code a sample for the presence of “sunshine” – what words would I need? Students brainstorm things like  start, sun, sunny, sunshine, etc., etc.

We discuss the importance of mutual exclusivity, being exhaustive, etc.

I show an example from my dissertation which looked at agenda setting topics on Twitter.

On the class day before I introduce Yoshikoder to the class, students do a practice assignment where I give them a list of random terms related to politics and elections. They then have to create “positive” and “negative” content categories using the terms. The terms aren’t necessarily well fit for this exercise, which gets them thinking a bit… They then hand code a sample of Tweets I provide about two different politicians. I tend to use the most recent election. So, in this case Obama and Romney. They are frustrated by having to hand code these Tweets – but a little trick is to do a search for the exact phrases in the Tweet files on the computer and they are done fairly quickly. Ok, so on the next class period:

1) Practice with Yoshikoder We do the same basic task, but this time they learn to program their “positive” and “negative” categories into Yoshikoder. They then load the Tweets (which I have saved as a txt file) and analyze them for the presence of their positive and negative content categories. This is a great point to stop and have students assess the reliability between what they hand coded and what the computer coded. Often, there will be discrepancies. And this makes for a great opportunity for discussion.

Here is the activity that I use in class. I also provide Tweets that I’ve downloaded using the search terms for the politician/candidate I’m using in the activity (e.g., Obama; Romney) in plain text format so Yoshikoder can read it. Also, see the below handout which I provide students to show them how to use Yoshikoder and how to program, and run the analyses I just described.

As I mentioned above, I create a handout that I like to give students that explains the different functionalities of Yoshikoder and how to run the analyses. As I’ve discussed elsewhere, I like to provide handouts. And the one below isn’t one of my more elaborate handouts. But it provides a quick overview with some screen shots to show what buttons need to be clicked. This is super helpful if you are trying to learn Yoshikoder, or want to use it alongside the activity (discussed in this post or the project discussed in my last post, and which I will provide in my next blog post).


Enjoy! .

EDIT: The assignment is now up. See the post.

If you’d like to learn more about using Yoshikoder, I found this great tutorial:

– Cheers! Matt