This is a copy of the social media audit assignment I have my students complete. The class is a university level strategic social media class. The students use Meltwater and other software to conduct the assignment.
You can read more about this assignment on my blog, MattKushin.com. Search: "Using Meltwater for a Social Media Audit Assignment in Social Media Class."
These slides were created for the course:
Comm 350R Social Media
Dr. Matthew J. Kushin
Department of Communication
Utah Valley University
For more on the course see:
http://profkushinsocial.wordpress.com
For more about the professor, see:
http://profkushin.wordpress.com
or @mjkushin on Twitter
Writing Across Platforms university communication writing course.
Teaches students keyword research for SEO, including what it is, what link building is, and why it matters. This lecture relates to two other lectures and with in class activities for students. See lecture "Writing for Search Engines: SEO, Google Trends, Adwords Keywords Tool" and "What is Keyword Research and SEO and why does it matter?" under my profile.
More on my blog: www.mattkushin.com
COVID-19 (Coronavirus) Brand Crisis Response Activity: Brands Doing Good in a...Matthew J. Kushin, Ph.D.
An informal group Zoom presentation activity for online students in a Public Relations Principles course. The activity asks students to explore and conduct a compare and contrast how brands are responding during the COVID-19 (coronavirus) crisis.
This is a copy of the social media audit assignment I have my students complete. The class is a university level strategic social media class. The students use Meltwater and other software to conduct the assignment.
You can read more about this assignment on my blog, MattKushin.com. Search: "Using Meltwater for a Social Media Audit Assignment in Social Media Class."
These slides were created for the course:
Comm 350R Social Media
Dr. Matthew J. Kushin
Department of Communication
Utah Valley University
For more on the course see:
http://profkushinsocial.wordpress.com
For more about the professor, see:
http://profkushin.wordpress.com
or @mjkushin on Twitter
Writing Across Platforms university communication writing course.
Teaches students keyword research for SEO, including what it is, what link building is, and why it matters. This lecture relates to two other lectures and with in class activities for students. See lecture "Writing for Search Engines: SEO, Google Trends, Adwords Keywords Tool" and "What is Keyword Research and SEO and why does it matter?" under my profile.
More on my blog: www.mattkushin.com
COVID-19 (Coronavirus) Brand Crisis Response Activity: Brands Doing Good in a...Matthew J. Kushin, Ph.D.
An informal group Zoom presentation activity for online students in a Public Relations Principles course. The activity asks students to explore and conduct a compare and contrast how brands are responding during the COVID-19 (coronavirus) crisis.
This is an updated version of my social media audit assignment for my university-level social media class. This assignment relies on the use of Keyhole.co social media analytics software. Learn more at: mattkushin.com.
These slides were created for the course:
Comm 350R Social Media
Dr. Matthew J. Kushin
Department of Communication
Utah Valley University
For more on the course see:
http://profkushinsocial.wordpress.com
For more about the professor, see:
http://profkushin.wordpress.com
or @mjkushin on Twitter
This is the full slide deck for my presentation at the 2016 PRSA Educator's Academy Super Saturday in Indianapolis. The presentation looks at how you can use the Slack app to foster class teams on group projects.
You can learn more at Mattkushin.com
These slides were created for the course:
Comm 350R Social Media
Dr. Matthew J. Kushin
Department of Communication
Utah Valley University
For more on the course see:
http://profkushinsocial.wordpress.com
For more about the professor, see:
http://profkushin.wordpress.com
or @mjkushin on Twitter
Crisis Communication Simulation Exercise [Freberg]Karen Freberg
This was the crisis simulation exercise I provided instead of a midterm for my graduate crisis communications class [#FrebergGrads] at the University of Louisville.
A beginner’s guide from a social network analysis fan with much to learn.
This handout accompanies slides and a video conference call I participated in about Netlytic and social network analysis basics.
This assignment provided by Meltwater will allow students to gain knowledge of the Meltwater platform using three dedicated case studies we suggest using this assignment over the course of several weeks. We have attached the case studies under documents for this assignment and they are named case study 1, case study 2 ,a and case study 3. Please download all of the content in order to teach this assignment.
Provided by Professor Michelle Groover at Georgia Southern University. This assignment allows students to perform a SWOT analysis while using Meltwater.
This is a syllabus for my persuasion and message design course. It looks at theories, concepts and tactics for persuasion.
To learn more about this class and others, go to: mattkushin.com
Students had access to the Sysomos Education program for Spring 2017. This tool was used to evaluate client and competitors on social media. Assignment created by @kfreberg.
My social media syllabus for fall 2017. Class is taught in the Department of Communication at Shepherd University. This semester, we will include Hootsuite Academy, Meltwater, and much more. Students can complete a Facebook Blueprint assignment for extra credit. This syllabus is discussed in depth on my blog: http://mattkushin.com
Determine the sentiment of sentence that is positive or negative based on the presence of part of
speech tag, the emoticons present in the sentences. For this research we use the most popular microblogging sit
twitter for sentiment orientation. In this paper we want to extract tweets form the twitter related to the product
like mobile phones, home appliances, vehicle etc. After retrieving tweets we perform some preprocessing on it
like remove retweets, remove tweets containing few words with minimum threshold of length five, remove tweets
containing only urls. After this the remaining tweets are pre-processed like that transform all letters of the
tweets to the lower case then remove punctuation from the tweets because it reduces the accuracy of result.
After this remove extra white spaces from the tweets, then we apply a pos tagger to tag each word. The tuple
after the applying above steps contain (word, pos tag, English-word, stop-word). We are interested in only
tweets that contain opinion and eliminate the remaining non-opinion tweets from the data set. For this we use
the Naïve Bays classification algorithm. After this we use short text classification on tweets i.e., the word having
different meaning in different domain. In order to solve this problem we use two different feature selection
algorithms the mutual information (MI) and the X2 feature selection. At final stage predicting the orientation of
an opinion sentence that is positive or negative as we mentioned above. For this we use two model like unigram
model and opinion miner.
This is an updated version of my social media audit assignment for my university-level social media class. This assignment relies on the use of Keyhole.co social media analytics software. Learn more at: mattkushin.com.
These slides were created for the course:
Comm 350R Social Media
Dr. Matthew J. Kushin
Department of Communication
Utah Valley University
For more on the course see:
http://profkushinsocial.wordpress.com
For more about the professor, see:
http://profkushin.wordpress.com
or @mjkushin on Twitter
This is the full slide deck for my presentation at the 2016 PRSA Educator's Academy Super Saturday in Indianapolis. The presentation looks at how you can use the Slack app to foster class teams on group projects.
You can learn more at Mattkushin.com
These slides were created for the course:
Comm 350R Social Media
Dr. Matthew J. Kushin
Department of Communication
Utah Valley University
For more on the course see:
http://profkushinsocial.wordpress.com
For more about the professor, see:
http://profkushin.wordpress.com
or @mjkushin on Twitter
Crisis Communication Simulation Exercise [Freberg]Karen Freberg
This was the crisis simulation exercise I provided instead of a midterm for my graduate crisis communications class [#FrebergGrads] at the University of Louisville.
A beginner’s guide from a social network analysis fan with much to learn.
This handout accompanies slides and a video conference call I participated in about Netlytic and social network analysis basics.
This assignment provided by Meltwater will allow students to gain knowledge of the Meltwater platform using three dedicated case studies we suggest using this assignment over the course of several weeks. We have attached the case studies under documents for this assignment and they are named case study 1, case study 2 ,a and case study 3. Please download all of the content in order to teach this assignment.
Provided by Professor Michelle Groover at Georgia Southern University. This assignment allows students to perform a SWOT analysis while using Meltwater.
This is a syllabus for my persuasion and message design course. It looks at theories, concepts and tactics for persuasion.
To learn more about this class and others, go to: mattkushin.com
Students had access to the Sysomos Education program for Spring 2017. This tool was used to evaluate client and competitors on social media. Assignment created by @kfreberg.
My social media syllabus for fall 2017. Class is taught in the Department of Communication at Shepherd University. This semester, we will include Hootsuite Academy, Meltwater, and much more. Students can complete a Facebook Blueprint assignment for extra credit. This syllabus is discussed in depth on my blog: http://mattkushin.com
Determine the sentiment of sentence that is positive or negative based on the presence of part of
speech tag, the emoticons present in the sentences. For this research we use the most popular microblogging sit
twitter for sentiment orientation. In this paper we want to extract tweets form the twitter related to the product
like mobile phones, home appliances, vehicle etc. After retrieving tweets we perform some preprocessing on it
like remove retweets, remove tweets containing few words with minimum threshold of length five, remove tweets
containing only urls. After this the remaining tweets are pre-processed like that transform all letters of the
tweets to the lower case then remove punctuation from the tweets because it reduces the accuracy of result.
After this remove extra white spaces from the tweets, then we apply a pos tagger to tag each word. The tuple
after the applying above steps contain (word, pos tag, English-word, stop-word). We are interested in only
tweets that contain opinion and eliminate the remaining non-opinion tweets from the data set. For this we use
the Naïve Bays classification algorithm. After this we use short text classification on tweets i.e., the word having
different meaning in different domain. In order to solve this problem we use two different feature selection
algorithms the mutual information (MI) and the X2 feature selection. At final stage predicting the orientation of
an opinion sentence that is positive or negative as we mentioned above. For this we use two model like unigram
model and opinion miner.
Focused on social media strategies and effective ways to monitor success for your non-profit or change-focused organization. Christopher Berry, Group Director of Marketing Science at Critical Mass will speak on practical social analytics.
A practical approach for professional communicators to pick out what matters (Presented on Jan. 18, 2011, to communications, marketing, design, and web staff at the University of British Columbia)
Context, social media culture, best practice-sharing & community engagement for Jewish startup projects (by Esther Kustanowitz, April 9, 2014, San Francisco)
Beyond Buzz - Web 2.0 Expo - K.Niederhoffer & M.Smithkategn
A framework to measure a conversation based on approaches from social psychology and sociology. Beyond quantity of buzz, we propose measuring the context of conversation: the signal, person, role, and ecosystem.
Sentiment Analysis on Twitter Dataset using R Languageijtsrd
Sentiment Analysis involves determining the evaluative nature of a piece of text. A product review can express a positive, negative, or neutral sentiment or polarity . Automatically identifying sentiment expressed in text has a number of applications, including tracking sentiment towards Movie reviews and Automobile reviews improving customer relation models, detecting happiness and well being, and improving automatic dialogue systems. The evaluative intensity for both positive and negative terms changes in a negated context, and the amount of change varies from term to term. To adequately capture the impact of negation on individual terms, here proposed to empirically estimate the sentiment scores of terms in negated context from movie review and auto mobile review, and built two lexicons, one for terms in negated contexts and one for terms in affirmative non negated contexts. By using these Affirmative Context Lexicons and Negated Context Lexicons were able to significantly improve the performance of the overall sentiment analysis system on both tasks. This thesis have proposed a sentiment analysis system that detects the sentiment of corpus dataset using movie review and Automobile review as well as the sentiment of a term a word or a phrase within a message term level task using R language. B. Nagajothi | Dr. R. Jemima Priyadarsini "Sentiment Analysis on Twitter Dataset using R Language" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28071.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/28071/sentiment-analysis-on-twitter-dataset-using-r-language/b-nagajothi
This course syllabus is for a university-level class on happiness and media use (aka, subjective well-being and communication). This class is titled Happiness: Media versus Reality because it compares portrayals of happiness in the media, media effects on happiness, and social scientific research on happiness. This is a special topics class. The class is taught at Shepherd University.
Learn more at https://mattkushin.com.
This is a public relations syllabus for the Principles of COMM 321: Public Relations course at Shepherd University. You can learn more about the class at mattkushin.com.
An introductory communication department syllabus for an Online Asynchronous (OLA) university course. The course is titled Communication & New Media. Learn more at: mattkushin.com
This assignment is for students to learn paid social media and influencer marketing using the Stukent Mimic Social simulator. This is for a social media public relations or social media marketing class. Learn more about this assignment by seraching "stukent mimic social" at Mattkushin.com
My Fall 2019 COMM 322 Social Media class syllabus for undergraduate students at Shepherd University. A version of this syllabus is discussed in detail in my book Teach Social Media: A Plan for Creating a Course Your Students Will Love available on Amazon.com.
Learn more about this class and read about assignments at: https://Mattkushin.com
This is a writing exercise used in my Writing Across Platforms class which teaches communication students to write a range of promotional content for print and the web. This assignment helps them work on writing leads by asking them to take an existing news story and re-write the headline and lead to focus on the most interesting part.
This is my syllabus for my Writing Across Platforms class. This class is aimed at undergraduate students studying communication, particularly those interested in careers in public relations, social media, strategic communication, and related fields. It teaches students to construct a variety of promotional writing pieces.
Read more about this and other classes at: https://mattkushin.com
This is the syllabus for my (applied) communication research class for spring 2019. The class is taught to undergraduate communication students at Shepherd University. The class is geared towards students interested in working in public relations, social media and related fields. Learn more about this class and others I teach at: https://mattkushin.com.
My Fall 2018 COMM 322 Social Media class syllabus for undergraduate students at Shepherd University. A version of this syllabus is discussed in detail in my book Teach Social Media: A Plan for Creating a Course Your Students Will Love available on Amazon.com.
Learn more about this class at: https://Mattkushin.com
This assignment was used in my Writing Across Platforms class. It is for the Mimic Intro Simulator, which is by Stukent.com. I am not affiliated with Stukent. But I did use their product in my class.
The simulator teaches student how to write PPC ads for search engine marketing.
You can read more about this and other assignments on my blog, MattKushin.com.
A beginner’s guide to social network analysis for social media and strat comm professors.
From a social network analysis fan with much to learn!
http://Netlytic.org
Overview of how to use the network visualization tool https://netlytic.org/home/?page_id=2
Tutorial for using Netlytic: https://youtu.be/F6scVtMGKFE
Additional Resources
♣ Basics of social network analysis slides
♣ Blog post “A Quick, Interactive Activity for Introducing the Concept of Digital Influencers”: http://mattkushin.com/2018/03/19/digital-influencers-easy-classroom-activity/
♣ Blog post detailing the below assignment: http://mattkushin.com/2017/04/24/teaching-basic-social-network-analysis-of-instagram-and-twitter-data-using-netlytic-org-post-4-of-4/
My online personal branding assignment used in my Public Relations Principles class. This assignment is adapted from adapted from A Roadmap for Teaching Social Media by Dr. Karen Freberg.
Read more at: MattKushin.com
This is an assignment for my PR Principles class at Shepherd University. Students participate in the Ketchum Mindfire Challenges. Learn more about the post at http://mattkushin.com. Search: Ketchum Mindfire.
This project was assigned to students in my communication research class. It combines several techniques to offer students a chance to learn a variety of different ways of doing social media analytics, social listening and some basic social network analysis.
You can learn more at: MattKushin.com
This is an example of a template that educator's can use to organize their classes, both in k-12 and college.
I blog about this topic at: http://mattkushin.com
Syllabus for my Fall 2016 social media class. Learn more about my class at mattkushin.com. A blog post on this class is here: http://mattkushin.com/2016/08/24/social-media-class-overview-fall-2016/
The Spring 2016 version of my Writing Across Platforms syllabus. This class is taught in the Department of Communication at Shepherd University. Learn more about it at mattkushin.com.
This form is used in team projects in my classes. You can learn more about how I use this assignment via a blog series I wrote at MattKushin.com titled "A Guide To Setting Up Classroom Groups for Success." It is discussed in post #3 of that series.
Intro to Sentiment Analysis: What it is, how to conduct it, and what are its limitations?
1. What are they saying?
Sentiment Analysis
Professor Matthew Kushin, PhD
Shepherd University | Department of Mass Communication | 2012
2. Preview
Last class:
Looked at what people say about a brand online
Today, we’ll explore:
Can we more systematically evaluate text content (such as
tweets)?
3. Defined
Sentiment analysis – process of categorizing text, based on
the “sentiment” or “feelings” embedded in the message.
Aka “opinion mining”
For assessing opinions
Form of content analysis – systematic process of coding
content of media for interpretation
4. Simple Example
Tweet:
“Can’t wait to see Zan the Ram at the game this weekend!!!”
Sentiment:
Positive
Problem
How do we know that this text is positive?
5. Basics: How it works
A database of words and symbols (e.g., !) is created.
Each word is assigned a value
Positive = 1
Negative = -1
Neutral = 0
Example: “love” = 1; “hate” =2; “blue” =0
6. How it works, contd
Computers or person evaluates each piece of data (e.g., a
Tweet), searching for words in database.
Total number of positive/negative/neutral counted in data,
and a sentiment score or % is given
7. Example
Tweets about Shepherdstown over a one-week period:
60% positive
20% negative
20% neutral
9. Potential, potential
Attitude towards your brand
Perception of products, ideas, brands, people, etc.
Reputation management
Able to respond to posts
Evaluate over time to see if sentiment is changing as part of
campaign goals
10. Example: Taco Bell Beef!
Last class
an unrepresentative sample of Tweets we happen to look at
Sentiment offers:
Much more systematic evaluation of tweets
Evaluate thousands of social media posts
Very quick & little cost
12. Tools
Many tools (paid and free) exist for assessing sentiment
Study of linguistics is applied backed by years of research &
understanding of human language.
Common limitations:
Language contains context
Is subjective
Inability to assess sarcasm & other nuances of human
communication
14. Key Considerations
We must interpret what the sentiment means
Sentiment alone is only a minor indicator of the true feelings
of the crowd.
Need to ask “Why is it positive/negative?”
“What products do people mention?”
15. Beyond Basic Sentiment
Computer-assisted content analysis of social media posts
virtually limitless potential
More detail than “pos” “neg” “neutral”
What about:
“satisfied” “dissatisfied” “concerned” “informed” “afraid” “glad”
etc.
Count all mentions of ANY term
Ex: product mentions in tweets: “Fries” “McRib” “McFlurry”
16. Participation: Obama v. Romney
Sentiment
Getting the PDF files:
Obama Tweets PDF: http://bit.ly/402_ObamaTweets
Romney Tweets PDF: http://bit.ly/402_RomneyTweets