SlideShare a Scribd company logo
Social Media Landscape
MEHMET BURAK AKGÜN
Awareness
Do enough people know about us? Do
enough people think about us?
Context
Do people think of us in the right way?
Value
Do people understand our value? What we
offer?
Relevance
Do people appreciate our value to them?
Catalysts
Do people have a reason to think about
us? To engage with us? To buy into us?
Brand Momentum Drivers
Social Media could
drive, amplify and reinforce
all of these things
2
Sales: Net New Customers, Increased Frequency of Transactions, promo
exposure. Increased yield (average $ value per transaction), and product
penetration
Customer Support: Immediate feedback and response, positive impact in
public forum, cost reduction
Human Resources: More effective recruiting, online monitoring of
employee behavior (risk management)
Public Relations: Online Reputation Management, improved brand image
via Social Web
Customer Loyalty: Increased interactions, better quality of interactions,
deeper relationship with brand. Increased trust in brand, increased mindshare
of brand, greater values alignment
Business Intelligence: Know Everything.
Ways Social Media Can Help Business
3
4
user-generated media
• Importance of opinions:
– Opinions are important because whenever we need to
make a decision, we want to hear others’ opinions.
– In the past,
• Individuals: opinions from friends and family
• businesses: surveys, focus groups, consultants …
• Word-of-mouth on the Web
– User-generated media: One can express opinions on anything in
reviews, forums, discussion groups, blogs ...
– Opinions of global scale: No longer limited to:
• Individuals: one’s circle of friends
• Businesses: Small scale surveys, tiny focus groups, etc.
An Example Review
• “I bought an iPhone a few days ago. It was such a nice
phone. The touch screen was really cool. The voice quality
was clear too. Although the battery life was not long, that
is ok for me. However, my mother was mad with me as I
did not tell her before I bought the phone. She also thought
the phone was too expensive, and wanted me to return it
to the shop. …”
• What do we see?
– Opinions, targets of opinions, and opinion holders
5
Can we successfully predict the
sentiment of an Instagram hashtag?
6
Instagram Overview
• Instagram – Photo sharing
social network
• Each post can contain a
caption and hashtags
• Hashtags group posts into
categories
• Express extra
information/emotion
about the post
7
Hashtag Overview
• Composed of words, phrases, and acronyms
• Often contain misspellings, made up words,
and slang/vernacular
#love
#myfriendsarehotterthanyourfriends
#likeabos
#ugly
#depresstion
#selfharmmm
8
% of Twitter Members Using Twitter to:
9
Text Data: Twitter
• A large and public social media service
– Good: Has people writing their thoughts
– Bad: News, celebrities, “media” stuff (?)
• Sources
1.Archiving the Twitter Streaming API
“Gardenhose”/”Sample”: ~10-15% of public tweets
1.Scrape of earlier messages
thanks to Brendan Meeder, CMU
• ~2 billion messages before topic selection,
Jan 2008 – May 2010
10
Message data
{
"text": "Time for the States to fight back !!! Tenth Amendment Movement: Taking On the
Feds http://bit.ly/14t1RV #tcot #teaparty”,
"created_at": "Tue Nov 17 21:08:39 +0000 2009",
"geo": null,
"id": 5806348114,
"in_reply_to_screen_name": null,
"in_reply_to_status_id": null,
"user": {
"screen_name": "TPO_News",
"created_at": "Fri May 15 04:16:38 +0000 2009",
"description": "Child of God - Married - Gun carrying NRA Conservative - Right Winger
hard Core Anti Obama (Pro America), Parrothead - www.ABoldStepBack.com #tcot #nra #iPhone",
"followers_count": 10470,
"friends_count": 11328,
"name": "Tom O'Halloran",
"profile_background_color": "f2f5f5",
"profile_image_url":
"http://a3.twimg.com/profile_images/295981637/TPO_Balcony_normal.jpg",
"protected": false,
"statuses_count": 21147,
"location": "Las Vegas, Baby!!",
"time_zone": "Pacific Time (US & Canada)",
"url": "http://www.tpo.net/1dollar",
"utc_offset": -28800,
}
} 11
Message data we use
{
"text": "Time for the States to fight back !!! Tenth Amendment Movement: Taking On the
Feds http://bit.ly/14t1RV #tcot #teaparty”,
"created_at": "Tue Nov 17 21:08:39 +0000 2009”
}
1. Text
2. Timestamp
• Message data we do not use:
– Locations from GPS
– Locations from IP addresses – not public
– User information (name, description, self-described location)
– Conversation structure: retweets, replies
– Social structure: follower network
12
Survey Data
• Consumer confidence, 2008-2009
– Index of Consumer Sentiment (Reuters/Michigan)
– Gallup Daily (free version from gallup.com)
• 2008 Presidential Elections
– Aggregation, Pollster.com
• 2009 Presidential Job Approval
– Gallup Daily
• Which tweets correspond to these polls?
13
Message selection via topic keywords
• Analyzed subsets of messages that contained
manually selected topic keyword
– “economy”, “jobs”, “job”
– “obama”
– “obama”, “mccain”
• High day-to-day volatility
– Fraction of messages containing keyword
– Nov 5 2008: 15% of tweets contain “obama”
14
Sentiment analysis: word counting
• Subjectivity Clues lexicon from OpinionFinder
(Univ. of Pittsburgh)
– Wilson et al 2005
– 2000 positive, 3600 negative words
• Procedure
1.Within topical messages,
2.Count messages containing these positive and
negative words
15
Sentiment Ratio over Messages
For one day t and a particular topic word, compute score
SentimentRatio( topic_word, t ) =
16
8% YoY Growth
Establish A Baseline
17
What are people talking about and where?
Map topics, keywords, trends, links, etc.
Monitor Impact On Conversations
18

More Related Content

What's hot

Sentiment analysis of Twitter Data
Sentiment analysis of Twitter DataSentiment analysis of Twitter Data
Sentiment analysis of Twitter Data
Nurendra Choudhary
 
Sentiment Analysis using Twitter Data
Sentiment Analysis using Twitter DataSentiment Analysis using Twitter Data
Sentiment Analysis using Twitter Data
Hari Prasad
 
sentiment analysis text extraction from social media
sentiment  analysis text extraction from social media sentiment  analysis text extraction from social media
sentiment analysis text extraction from social media
Ravindra Chaudhary
 
Sentiment Analysis on Twitter
Sentiment Analysis on TwitterSentiment Analysis on Twitter
Sentiment Analysis on Twitter
SmritiAgarwal26
 
Sentiment analysis of twitter data
Sentiment analysis of twitter dataSentiment analysis of twitter data
Sentiment analysis of twitter data
Bhagyashree Deokar
 
Approaches to Sentiment Analysis
Approaches to Sentiment AnalysisApproaches to Sentiment Analysis
Approaches to Sentiment Analysis
Nihar Suryawanshi
 
Sentiment Analysis in Twitter
Sentiment Analysis in TwitterSentiment Analysis in Twitter
Sentiment Analysis in Twitter
Ayushi Dalmia
 
Sentiment analysis
Sentiment analysisSentiment analysis
Sentiment analysis
Makrand Patil
 
Practical sentiment analysis
Practical sentiment analysisPractical sentiment analysis
Practical sentiment analysis
Diana Maynard
 
Amazon sentimental analysis
Amazon sentimental analysisAmazon sentimental analysis
Amazon sentimental analysis
Akhila
 
Sentiment Analysis of Feedback Data
Sentiment Analysis of Feedback DataSentiment Analysis of Feedback Data
Sentiment Analysis of Feedback Data
ijtsrd
 
Twitter sentiment analysis
Twitter sentiment analysisTwitter sentiment analysis
Twitter sentiment analysis
Sunil Kandari
 
How Does Customer Feedback Sentiment Analysis Work in Search Marketing?
How Does Customer Feedback Sentiment Analysis Work in Search Marketing?How Does Customer Feedback Sentiment Analysis Work in Search Marketing?
How Does Customer Feedback Sentiment Analysis Work in Search Marketing?
Countants
 
Tweet sentiment analysis
Tweet sentiment analysisTweet sentiment analysis
Tweet sentiment analysis
Anil Shrestha
 
Introduction to Sentiment Analysis
Introduction to Sentiment AnalysisIntroduction to Sentiment Analysis
Introduction to Sentiment Analysis
Jaganadh Gopinadhan
 
Sentimental Analysis of twitter data .
Sentimental Analysis of twitter data .Sentimental Analysis of twitter data .
Sentimental Analysis of twitter data .
Greater Noida Institute Of Technology
 
Sentiment Analysis
Sentiment AnalysisSentiment Analysis
Sentiment Analysis
Data Science Society
 
New sentiment analysis of tweets using python by Ravi kumar
New sentiment analysis of tweets using python by Ravi kumarNew sentiment analysis of tweets using python by Ravi kumar
New sentiment analysis of tweets using python by Ravi kumar
Ravi Kumar
 
social network analysis project twitter sentimental analysis
social network analysis project twitter sentimental analysissocial network analysis project twitter sentimental analysis
social network analysis project twitter sentimental analysis
Ashish Mundra
 
Social Media Analytics
Social Media AnalyticsSocial Media Analytics
Social Media Analytics
Kelli Burns
 

What's hot (20)

Sentiment analysis of Twitter Data
Sentiment analysis of Twitter DataSentiment analysis of Twitter Data
Sentiment analysis of Twitter Data
 
Sentiment Analysis using Twitter Data
Sentiment Analysis using Twitter DataSentiment Analysis using Twitter Data
Sentiment Analysis using Twitter Data
 
sentiment analysis text extraction from social media
sentiment  analysis text extraction from social media sentiment  analysis text extraction from social media
sentiment analysis text extraction from social media
 
Sentiment Analysis on Twitter
Sentiment Analysis on TwitterSentiment Analysis on Twitter
Sentiment Analysis on Twitter
 
Sentiment analysis of twitter data
Sentiment analysis of twitter dataSentiment analysis of twitter data
Sentiment analysis of twitter data
 
Approaches to Sentiment Analysis
Approaches to Sentiment AnalysisApproaches to Sentiment Analysis
Approaches to Sentiment Analysis
 
Sentiment Analysis in Twitter
Sentiment Analysis in TwitterSentiment Analysis in Twitter
Sentiment Analysis in Twitter
 
Sentiment analysis
Sentiment analysisSentiment analysis
Sentiment analysis
 
Practical sentiment analysis
Practical sentiment analysisPractical sentiment analysis
Practical sentiment analysis
 
Amazon sentimental analysis
Amazon sentimental analysisAmazon sentimental analysis
Amazon sentimental analysis
 
Sentiment Analysis of Feedback Data
Sentiment Analysis of Feedback DataSentiment Analysis of Feedback Data
Sentiment Analysis of Feedback Data
 
Twitter sentiment analysis
Twitter sentiment analysisTwitter sentiment analysis
Twitter sentiment analysis
 
How Does Customer Feedback Sentiment Analysis Work in Search Marketing?
How Does Customer Feedback Sentiment Analysis Work in Search Marketing?How Does Customer Feedback Sentiment Analysis Work in Search Marketing?
How Does Customer Feedback Sentiment Analysis Work in Search Marketing?
 
Tweet sentiment analysis
Tweet sentiment analysisTweet sentiment analysis
Tweet sentiment analysis
 
Introduction to Sentiment Analysis
Introduction to Sentiment AnalysisIntroduction to Sentiment Analysis
Introduction to Sentiment Analysis
 
Sentimental Analysis of twitter data .
Sentimental Analysis of twitter data .Sentimental Analysis of twitter data .
Sentimental Analysis of twitter data .
 
Sentiment Analysis
Sentiment AnalysisSentiment Analysis
Sentiment Analysis
 
New sentiment analysis of tweets using python by Ravi kumar
New sentiment analysis of tweets using python by Ravi kumarNew sentiment analysis of tweets using python by Ravi kumar
New sentiment analysis of tweets using python by Ravi kumar
 
social network analysis project twitter sentimental analysis
social network analysis project twitter sentimental analysissocial network analysis project twitter sentimental analysis
social network analysis project twitter sentimental analysis
 
Social Media Analytics
Social Media AnalyticsSocial Media Analytics
Social Media Analytics
 

Viewers also liked

#ThinkPH Social Media Sentiment Analysis
#ThinkPH Social Media Sentiment Analysis#ThinkPH Social Media Sentiment Analysis
#ThinkPH Social Media Sentiment Analysis
Robin Leonard
 
Sentiment Analysis and Political Disaffection in Italy
Sentiment Analysis and Political Disaffection in ItalySentiment Analysis and Political Disaffection in Italy
Sentiment Analysis and Political Disaffection in Italy
Corrado Monti
 
Vendor classification & rating
Vendor classification & ratingVendor classification & rating
Vendor classification & ratingAmit Puri
 
Onicra Vendor Rating
Onicra Vendor RatingOnicra Vendor Rating
Onicra Vendor Rating
vikasbayyarapu
 
Vendor/Supplier rating
Vendor/Supplier ratingVendor/Supplier rating
Vendor/Supplier rating
suresh t
 
Social media & sentiment analysis splunk conf2012
Social media & sentiment analysis   splunk conf2012Social media & sentiment analysis   splunk conf2012
Social media & sentiment analysis splunk conf2012
Michael Wilde
 
How to evaluate and select vendors with TransparentChoice software
How to evaluate and select vendors with TransparentChoice softwareHow to evaluate and select vendors with TransparentChoice software
How to evaluate and select vendors with TransparentChoice software
TransparentChoice
 
Vendor rating system
Vendor rating systemVendor rating system
Vendor rating system
Chandrmouli Singh
 
Twitter sentiment-analysis Jiit2013-14
Twitter sentiment-analysis Jiit2013-14Twitter sentiment-analysis Jiit2013-14
Twitter sentiment-analysis Jiit2013-14Rachit Goel
 

Viewers also liked (10)

#ThinkPH Social Media Sentiment Analysis
#ThinkPH Social Media Sentiment Analysis#ThinkPH Social Media Sentiment Analysis
#ThinkPH Social Media Sentiment Analysis
 
Sentiment Analysis and Political Disaffection in Italy
Sentiment Analysis and Political Disaffection in ItalySentiment Analysis and Political Disaffection in Italy
Sentiment Analysis and Political Disaffection in Italy
 
Vendor classification & rating
Vendor classification & ratingVendor classification & rating
Vendor classification & rating
 
Onicra Vendor Rating
Onicra Vendor RatingOnicra Vendor Rating
Onicra Vendor Rating
 
Vendor/Supplier rating
Vendor/Supplier ratingVendor/Supplier rating
Vendor/Supplier rating
 
Social media & sentiment analysis splunk conf2012
Social media & sentiment analysis   splunk conf2012Social media & sentiment analysis   splunk conf2012
Social media & sentiment analysis splunk conf2012
 
How to evaluate and select vendors with TransparentChoice software
How to evaluate and select vendors with TransparentChoice softwareHow to evaluate and select vendors with TransparentChoice software
How to evaluate and select vendors with TransparentChoice software
 
Vendor rating
Vendor ratingVendor rating
Vendor rating
 
Vendor rating system
Vendor rating systemVendor rating system
Vendor rating system
 
Twitter sentiment-analysis Jiit2013-14
Twitter sentiment-analysis Jiit2013-14Twitter sentiment-analysis Jiit2013-14
Twitter sentiment-analysis Jiit2013-14
 

Similar to Social Media Sentiment Analysis

Information is Everything: Marketing in the Age of Disruption
Information is Everything: Marketing in the Age of DisruptionInformation is Everything: Marketing in the Age of Disruption
Information is Everything: Marketing in the Age of Disruption
Tahzoo
 
Lastest and Coolest In Internet Marketing
Lastest and Coolest In Internet MarketingLastest and Coolest In Internet Marketing
Lastest and Coolest In Internet Marketing
hillarybressler
 
Intro to Social Media for PR
Intro to Social Media for PRIntro to Social Media for PR
Intro to Social Media for PRprofhutchins
 
03 dllo davidlafontaine
03 dllo davidlafontaine03 dllo davidlafontaine
03 dllo davidlafontaine
Ministerio TIC Colombia
 
Loyalty world
Loyalty world Loyalty world
Loyalty world Tony Fish
 
Socialmedia 101 - MATI
Socialmedia 101  - MATI Socialmedia 101  - MATI
Socialmedia 101 - MATI
Shari Wright-Pilo
 
jumpinteractive at USF - Socialize Your ROI
jumpinteractive at USF - Socialize Your ROIjumpinteractive at USF - Socialize Your ROI
jumpinteractive at USF - Socialize Your ROI
atLarge, Inc.
 
Know the "WHY" Behind Consumer Purchase Decisions
Know the "WHY" Behind Consumer Purchase DecisionsKnow the "WHY" Behind Consumer Purchase Decisions
Know the "WHY" Behind Consumer Purchase Decisions
NetBase Solutions Inc.
 
Mobile, Mobile, Data
Mobile, Mobile, DataMobile, Mobile, Data
Mobile, Mobile, Data
Tony Fish
 
Social Media... Woop! Woop! (February 2012)
Social Media... Woop! Woop! (February 2012)Social Media... Woop! Woop! (February 2012)
Social Media... Woop! Woop! (February 2012)Ed Cook
 
Writing across media
Writing across mediaWriting across media
Writing across media
Marc Wright
 
Sascon 2014 you are what google says you are
Sascon 2014   you are what google says you areSascon 2014   you are what google says you are
Sascon 2014 you are what google says you areNick Garner
 
Getting It Jobs In Social Media
Getting It Jobs In Social MediaGetting It Jobs In Social Media
Getting It Jobs In Social Media
Kelly Ripley Feller
 
Museum Website Best Practices for the 21st Century
Museum Website Best Practices for the 21st CenturyMuseum Website Best Practices for the 21st Century
Museum Website Best Practices for the 21st Century
Dana Mitroff Silvers
 
EO Toronto: Social media - fad or fantastic
EO Toronto: Social media - fad or fantasticEO Toronto: Social media - fad or fantastic
EO Toronto: Social media - fad or fantastic
ClearFit
 
Social Media Introduction, Holistic Digital
Social Media Introduction, Holistic DigitalSocial Media Introduction, Holistic Digital
Social Media Introduction, Holistic Digital
Schematiq
 
Social Business: What is the buzz about Social Biz?
Social Business: What is the buzz about Social Biz?Social Business: What is the buzz about Social Biz?
Social Business: What is the buzz about Social Biz?
Elizabeth Quintanilla, MBA
 
Social Media & Electronics Industry - presented at AECOC Madrid 9010 Group
Social Media & Electronics Industry - presented at AECOC Madrid 9010 GroupSocial Media & Electronics Industry - presented at AECOC Madrid 9010 Group
Social Media & Electronics Industry - presented at AECOC Madrid 9010 Group
Symbio Agency Ltd
 
Webinar on corruption and commercialization online
Webinar on corruption and commercialization onlineWebinar on corruption and commercialization online
Webinar on corruption and commercialization online
David Kamerer
 

Similar to Social Media Sentiment Analysis (20)

Information is Everything: Marketing in the Age of Disruption
Information is Everything: Marketing in the Age of DisruptionInformation is Everything: Marketing in the Age of Disruption
Information is Everything: Marketing in the Age of Disruption
 
Lastest and Coolest In Internet Marketing
Lastest and Coolest In Internet MarketingLastest and Coolest In Internet Marketing
Lastest and Coolest In Internet Marketing
 
Intro to Social Media for PR
Intro to Social Media for PRIntro to Social Media for PR
Intro to Social Media for PR
 
03 dllo davidlafontaine
03 dllo davidlafontaine03 dllo davidlafontaine
03 dllo davidlafontaine
 
Loyalty world
Loyalty world Loyalty world
Loyalty world
 
Socialmedia 101 - MATI
Socialmedia 101  - MATI Socialmedia 101  - MATI
Socialmedia 101 - MATI
 
jumpinteractive at USF - Socialize Your ROI
jumpinteractive at USF - Socialize Your ROIjumpinteractive at USF - Socialize Your ROI
jumpinteractive at USF - Socialize Your ROI
 
Know the "WHY" Behind Consumer Purchase Decisions
Know the "WHY" Behind Consumer Purchase DecisionsKnow the "WHY" Behind Consumer Purchase Decisions
Know the "WHY" Behind Consumer Purchase Decisions
 
Mobile, Mobile, Data
Mobile, Mobile, DataMobile, Mobile, Data
Mobile, Mobile, Data
 
Social Media... Woop! Woop! (February 2012)
Social Media... Woop! Woop! (February 2012)Social Media... Woop! Woop! (February 2012)
Social Media... Woop! Woop! (February 2012)
 
Writing across media
Writing across mediaWriting across media
Writing across media
 
Sascon 2014 you are what google says you are
Sascon 2014   you are what google says you areSascon 2014   you are what google says you are
Sascon 2014 you are what google says you are
 
Getting It Jobs In Social Media
Getting It Jobs In Social MediaGetting It Jobs In Social Media
Getting It Jobs In Social Media
 
Museum Website Best Practices for the 21st Century
Museum Website Best Practices for the 21st CenturyMuseum Website Best Practices for the 21st Century
Museum Website Best Practices for the 21st Century
 
EO Toronto: Social media - fad or fantastic
EO Toronto: Social media - fad or fantasticEO Toronto: Social media - fad or fantastic
EO Toronto: Social media - fad or fantastic
 
Social Media Introduction, Holistic Digital
Social Media Introduction, Holistic DigitalSocial Media Introduction, Holistic Digital
Social Media Introduction, Holistic Digital
 
Quick evaluation
Quick evaluationQuick evaluation
Quick evaluation
 
Social Business: What is the buzz about Social Biz?
Social Business: What is the buzz about Social Biz?Social Business: What is the buzz about Social Biz?
Social Business: What is the buzz about Social Biz?
 
Social Media & Electronics Industry - presented at AECOC Madrid 9010 Group
Social Media & Electronics Industry - presented at AECOC Madrid 9010 GroupSocial Media & Electronics Industry - presented at AECOC Madrid 9010 Group
Social Media & Electronics Industry - presented at AECOC Madrid 9010 Group
 
Webinar on corruption and commercialization online
Webinar on corruption and commercialization onlineWebinar on corruption and commercialization online
Webinar on corruption and commercialization online
 

Recently uploaded

1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx
JosvitaDsouza2
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
Ashokrao Mane college of Pharmacy Peth-Vadgaon
 
Guidance_and_Counselling.pdf B.Ed. 4th Semester
Guidance_and_Counselling.pdf B.Ed. 4th SemesterGuidance_and_Counselling.pdf B.Ed. 4th Semester
Guidance_and_Counselling.pdf B.Ed. 4th Semester
Atul Kumar Singh
 
The approach at University of Liverpool.pptx
The approach at University of Liverpool.pptxThe approach at University of Liverpool.pptx
The approach at University of Liverpool.pptx
Jisc
 
Best Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDABest Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDA
deeptiverma2406
 
A Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in EducationA Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in Education
Peter Windle
 
S1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptxS1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptx
tarandeep35
 
Multithreading_in_C++ - std::thread, race condition
Multithreading_in_C++ - std::thread, race conditionMultithreading_in_C++ - std::thread, race condition
Multithreading_in_C++ - std::thread, race condition
Mohammed Sikander
 
Digital Tools and AI for Teaching Learning and Research
Digital Tools and AI for Teaching Learning and ResearchDigital Tools and AI for Teaching Learning and Research
Digital Tools and AI for Teaching Learning and Research
Vikramjit Singh
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
TechSoup
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
heathfieldcps1
 
Language Across the Curriculm LAC B.Ed.
Language Across the  Curriculm LAC B.Ed.Language Across the  Curriculm LAC B.Ed.
Language Across the Curriculm LAC B.Ed.
Atul Kumar Singh
 
Digital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion DesignsDigital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion Designs
chanes7
 
Unit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdfUnit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdf
Thiyagu K
 
Home assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdfHome assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdf
Tamralipta Mahavidyalaya
 
Honest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptxHonest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptx
timhan337
 
Group Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana BuscigliopptxGroup Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana Buscigliopptx
ArianaBusciglio
 
A Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptxA Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptx
thanhdowork
 
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptxChapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptx
Mohd Adib Abd Muin, Senior Lecturer at Universiti Utara Malaysia
 
Synthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptxSynthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptx
Pavel ( NSTU)
 

Recently uploaded (20)

1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
 
Guidance_and_Counselling.pdf B.Ed. 4th Semester
Guidance_and_Counselling.pdf B.Ed. 4th SemesterGuidance_and_Counselling.pdf B.Ed. 4th Semester
Guidance_and_Counselling.pdf B.Ed. 4th Semester
 
The approach at University of Liverpool.pptx
The approach at University of Liverpool.pptxThe approach at University of Liverpool.pptx
The approach at University of Liverpool.pptx
 
Best Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDABest Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDA
 
A Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in EducationA Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in Education
 
S1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptxS1-Introduction-Biopesticides in ICM.pptx
S1-Introduction-Biopesticides in ICM.pptx
 
Multithreading_in_C++ - std::thread, race condition
Multithreading_in_C++ - std::thread, race conditionMultithreading_in_C++ - std::thread, race condition
Multithreading_in_C++ - std::thread, race condition
 
Digital Tools and AI for Teaching Learning and Research
Digital Tools and AI for Teaching Learning and ResearchDigital Tools and AI for Teaching Learning and Research
Digital Tools and AI for Teaching Learning and Research
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
 
Language Across the Curriculm LAC B.Ed.
Language Across the  Curriculm LAC B.Ed.Language Across the  Curriculm LAC B.Ed.
Language Across the Curriculm LAC B.Ed.
 
Digital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion DesignsDigital Artifact 2 - Investigating Pavilion Designs
Digital Artifact 2 - Investigating Pavilion Designs
 
Unit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdfUnit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdf
 
Home assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdfHome assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdf
 
Honest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptxHonest Reviews of Tim Han LMA Course Program.pptx
Honest Reviews of Tim Han LMA Course Program.pptx
 
Group Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana BuscigliopptxGroup Presentation 2 Economics.Ariana Buscigliopptx
Group Presentation 2 Economics.Ariana Buscigliopptx
 
A Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptxA Survey of Techniques for Maximizing LLM Performance.pptx
A Survey of Techniques for Maximizing LLM Performance.pptx
 
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptxChapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptx
 
Synthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptxSynthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptx
 

Social Media Sentiment Analysis

  • 2. Awareness Do enough people know about us? Do enough people think about us? Context Do people think of us in the right way? Value Do people understand our value? What we offer? Relevance Do people appreciate our value to them? Catalysts Do people have a reason to think about us? To engage with us? To buy into us? Brand Momentum Drivers Social Media could drive, amplify and reinforce all of these things 2
  • 3. Sales: Net New Customers, Increased Frequency of Transactions, promo exposure. Increased yield (average $ value per transaction), and product penetration Customer Support: Immediate feedback and response, positive impact in public forum, cost reduction Human Resources: More effective recruiting, online monitoring of employee behavior (risk management) Public Relations: Online Reputation Management, improved brand image via Social Web Customer Loyalty: Increased interactions, better quality of interactions, deeper relationship with brand. Increased trust in brand, increased mindshare of brand, greater values alignment Business Intelligence: Know Everything. Ways Social Media Can Help Business 3
  • 4. 4 user-generated media • Importance of opinions: – Opinions are important because whenever we need to make a decision, we want to hear others’ opinions. – In the past, • Individuals: opinions from friends and family • businesses: surveys, focus groups, consultants … • Word-of-mouth on the Web – User-generated media: One can express opinions on anything in reviews, forums, discussion groups, blogs ... – Opinions of global scale: No longer limited to: • Individuals: one’s circle of friends • Businesses: Small scale surveys, tiny focus groups, etc.
  • 5. An Example Review • “I bought an iPhone a few days ago. It was such a nice phone. The touch screen was really cool. The voice quality was clear too. Although the battery life was not long, that is ok for me. However, my mother was mad with me as I did not tell her before I bought the phone. She also thought the phone was too expensive, and wanted me to return it to the shop. …” • What do we see? – Opinions, targets of opinions, and opinion holders 5
  • 6. Can we successfully predict the sentiment of an Instagram hashtag? 6
  • 7. Instagram Overview • Instagram – Photo sharing social network • Each post can contain a caption and hashtags • Hashtags group posts into categories • Express extra information/emotion about the post 7
  • 8. Hashtag Overview • Composed of words, phrases, and acronyms • Often contain misspellings, made up words, and slang/vernacular #love #myfriendsarehotterthanyourfriends #likeabos #ugly #depresstion #selfharmmm 8
  • 9. % of Twitter Members Using Twitter to: 9
  • 10. Text Data: Twitter • A large and public social media service – Good: Has people writing their thoughts – Bad: News, celebrities, “media” stuff (?) • Sources 1.Archiving the Twitter Streaming API “Gardenhose”/”Sample”: ~10-15% of public tweets 1.Scrape of earlier messages thanks to Brendan Meeder, CMU • ~2 billion messages before topic selection, Jan 2008 – May 2010 10
  • 11. Message data { "text": "Time for the States to fight back !!! Tenth Amendment Movement: Taking On the Feds http://bit.ly/14t1RV #tcot #teaparty”, "created_at": "Tue Nov 17 21:08:39 +0000 2009", "geo": null, "id": 5806348114, "in_reply_to_screen_name": null, "in_reply_to_status_id": null, "user": { "screen_name": "TPO_News", "created_at": "Fri May 15 04:16:38 +0000 2009", "description": "Child of God - Married - Gun carrying NRA Conservative - Right Winger hard Core Anti Obama (Pro America), Parrothead - www.ABoldStepBack.com #tcot #nra #iPhone", "followers_count": 10470, "friends_count": 11328, "name": "Tom O'Halloran", "profile_background_color": "f2f5f5", "profile_image_url": "http://a3.twimg.com/profile_images/295981637/TPO_Balcony_normal.jpg", "protected": false, "statuses_count": 21147, "location": "Las Vegas, Baby!!", "time_zone": "Pacific Time (US & Canada)", "url": "http://www.tpo.net/1dollar", "utc_offset": -28800, } } 11
  • 12. Message data we use { "text": "Time for the States to fight back !!! Tenth Amendment Movement: Taking On the Feds http://bit.ly/14t1RV #tcot #teaparty”, "created_at": "Tue Nov 17 21:08:39 +0000 2009” } 1. Text 2. Timestamp • Message data we do not use: – Locations from GPS – Locations from IP addresses – not public – User information (name, description, self-described location) – Conversation structure: retweets, replies – Social structure: follower network 12
  • 13. Survey Data • Consumer confidence, 2008-2009 – Index of Consumer Sentiment (Reuters/Michigan) – Gallup Daily (free version from gallup.com) • 2008 Presidential Elections – Aggregation, Pollster.com • 2009 Presidential Job Approval – Gallup Daily • Which tweets correspond to these polls? 13
  • 14. Message selection via topic keywords • Analyzed subsets of messages that contained manually selected topic keyword – “economy”, “jobs”, “job” – “obama” – “obama”, “mccain” • High day-to-day volatility – Fraction of messages containing keyword – Nov 5 2008: 15% of tweets contain “obama” 14
  • 15. Sentiment analysis: word counting • Subjectivity Clues lexicon from OpinionFinder (Univ. of Pittsburgh) – Wilson et al 2005 – 2000 positive, 3600 negative words • Procedure 1.Within topical messages, 2.Count messages containing these positive and negative words 15
  • 16. Sentiment Ratio over Messages For one day t and a particular topic word, compute score SentimentRatio( topic_word, t ) = 16
  • 17. 8% YoY Growth Establish A Baseline 17
  • 18. What are people talking about and where? Map topics, keywords, trends, links, etc. Monitor Impact On Conversations 18

Editor's Notes

  1. Nov 5 2008, “obama” volume is 14.6%, but median obama volume is 0.3%