#supplychain and Twitter Analytics

Insights from hashtag #supplychain and Twitter Analytics: Considering Twitter and Twitter data for supply chain practice and research

Bongsug (Kevin) ChaePresented by: Dennis L. Kappen, Ph.D. Candidate, GAMER Lab, FBIT

Twitter :3d_ideation

Image Source: http://room214.com/social/getting-to-know-twitter-analytics

05/02/2023 Dennis L. Kappen Twitter :3d_ideation 2

Terminology

Image Source: http://cdn2.business2community.com/wp-content/uploads/2015/02/twitter-analytics.png.png

Moving Product or Service > to CustomerSupply Chain Management > SCM


TakeawaysExtracting intelligence

from 22,399 #supplychain tweets.Framework

descriptive analytics (DA), content analytics (CA) integrating

text mining and sentiment analysis,

network analytics (NA)Findings

Usage of supply chain tweetsImage Source: http://cdn2.business2community.com/wp-content/uploads/2015/02/twitter-analytics.png.png

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Overview

Dennis L. Kappen Twitter :3d_ideation

Introduction Background Framework Research method

(Results) Discussion Implications Limitations and Future

WorkImage Source: https://media.licdn.com/mpr/mpr/AAEAAQAAAAAAAAQWAAAAJGE4ODJkOWY0LTVmYTctNDA5NC04ZDRkLWMwNWEwZWU5MzY1NQ.jpg

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Introduction: Social Media and Big Data


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Introduction: Social Media and SCM


Slow growth in the usage of social media

Focus on: product traceability data geo-location and mapping data supply chain visibility and intelligence

Image Source: https://pharmapromotional.files.wordpress.com/2013/08/pharma_supply_chain_information_flow.png

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Introduction: Why Twitter?


Access to Twitter data using Twitter Application Programming Interface (API)

Understand Twitter within SCM context

Analyse: tweets, replies, and retweets

Image Source: http://www.glitztechnology.com/images/twitterapi-539x230.jpg

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Introduction: Research Direction


Research direction: Tweet characteristics Topics characteristics User characteristics Sentiment characteristics.

Image Source: http://www.glitztechnology.com/images/twitterapi-539x230.jpg

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Framework: Why?


Twitter Firehoses are expensive

Analysis is expensive

Extract intelligence from the highly enriched and unstructured social media data

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Framework: What?


Framework: Descriptive analytics (DA) Content analytics (CA) Network analytics (NA)

Image Source: https://upload.wikimedia.org/wikipedia/commons/b/b7/Lorimerlite_framework.JPG

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Descriptive analytics (DA) Descriptive Statistics Tweet metrics▪ INTELLIGENCE extraction▪ METRICS: number of tweets, word

counts, @user per tweet, number of hashtags, etc.▪ WHO tweets, replies, and retweets?▪ WHICH URLs?

Framework: What?


Image Source: http://wersm.com/wp-content/uploads/2013/11/twitter-analytics-657x360.jpg

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Content analytics (CA) Texts are unstructured Text cleaning and

processing Information and opinions Advanced text mining: sentiment analysis

Twitter Analytics relies on automatic text processing techniques and algorithms

Framework: What?


Image Source: http://www.contentanalyticsinc.com/about

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Network analytics (NA) Users engage

using@reply and retweet Network topology▪ Nodes (users)▪ Edges (relationships)

Twitter data▪ friendship network and @reply

(or mention) network.

Framework: What?



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Network analytics (NA) Centrality analysis Community analysis Modularity analysis

Framework: What?



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Framework: Recap


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Framework: Recap


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Framework: Recap


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500 million tweets/day (2015)

#supplychain 22,399 tweets

Script languagesTweet Statistics

Original tweets (58%) Retweets (28%) @replies (14%)

Results… DA (Tweets)


Image Source: http://yogfitness.com/wp-content/uploads/2016/04/historical-tweets.jpg

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4313 unique usersActive users = original tweets + retweets+@replies

Visibility = @replies received + retweets received

Results... DA (Users)


Image Source: http://yogfitness.com/wp-content/uploads/2016/04/historical-tweets.jpg

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Results... DA (Users)


Active users = original tweets + retweets+@replies Visibility = @replies received + retweets received

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Results... DA (URLs)


One or more URLs = 89% Active and Visible users include URLs

in their tweets Top URLs include:

companies' webpages SCM online newspaper sites, and articles about manufacturing leadership, and Big Data.

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Results... CA (Word analysis)


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Results... CA (Hashtag analysis)


3839 different hashtags appear 62,575 times

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Results... CA (Sentiment Analysis)


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Exemplar tweets Sentiment

This development is pretty exciting for me #supplychain #sustainability

3 (Positive)

Samsung assures excellent working conditions in China. http://t.co/9VcBIL1XAj #workingconditions #supplychain ⟨

#responsiblesourcing #rtw ⟩

3 (Positive)

Loving the feedback that I am getting on this report today! #supplychain http://t.co/7DJaJFFl ⟨ ⟩

3 (Positive)

As parked 787 s multiply? Boeing cash drain worries grow http://t.co/up6V9sBYbi #supplychain⟨ ⟩

-3 (Negative)

CHaINA Magazine: Apple Finds Child Labor Abuses in Its Supply Chain – As the controversy regarding. http://t.co/kt6MMXvng ⟨#SupplyChain⟩

-3 (Negative)

Walmart US Chief Says Sales are Suffering Because of Restocking Issues http://t.co/xhpK4pYy3v #supplychain⟨ ⟩

-3 (Negative)

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Exemplar tweets Sentiment

CSR Investigation of #Apple #SupplyChain by #SACOM reveals continued #labor abuse throughout despite Apple's claims. http://t.co/Cm0VYeTT94 #CSR⟨ ⟩

Negative

Loving this Green Supply Chain infographic http://t.co/M0spSUs6WG #supplychain #CSR #infographic ⟨

@SCInsightsLLC⟩

Positive

IT Supply Chain Disruption a Major Threat to Business from @forbes http://t.co/raX48u4Zcw #supplychain #IT ⟨#analytics⟩

Negative

How @Sony strengthened its supply chain and added value http://t.co/B0DTiWPAnm #GrnBz via @GreenBiz #IT ⟨

#supplychain⟩

Positive

Logistics

Could I expect to receive my parcel today? I doubt it. Another terrible experience from @Parcel2Go #expensive #supplychain #logistics

Negative

Great day @ #DalhousieUniversity! Excellent case study presentations by 16 teams. Join Careers in Motion @JDIcareers #logistics #supplychain

Positive

Risk With new #supplychain controls in place IKEA meatballs back after horsemeat scare http://t.co/YKvYT1ov1H #risk⟨ ⟩

Negative

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Results... NA (Topological Analysis)


5447 Nodes = users 9238 edges = relationships (@reply) Network diameter = 19 Average path length =5.82

Example: 6 nodes, 7 edges : StackOverflow

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Results... NA (Centrality analysis)


Image Source: http://image.slidesharecdn.com/socialnetworkanalysis-100225055227-phpapp02/95/social-network-analysis-19-638.jpg?cb=1385568277

Degree Centrality In-degree Out-degree

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Results... NA


Centrality Analysis (node-level) Nodes connectedness

Community Analysis (network-level) Network was sparsely distributed Over 400 communities in the

#supplychain network

Image Source: http://www.compjournalism.com/wp-content/uploads/2012/11/centrality-measures.png

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Results... NA

Dennis L. Kappen Twitter :3d_ideationCompanies Industry PressIndividual users

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Results... NA (Community analysis)


(Blondel et al., 2008)

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Results... NA (Community analysis)


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Discussion...(Characteristics)


Image Source: http://www.supplychain247.com/images/article/a_portrait_of_the_supply_chain_manager_wide_image.jpg

Topical 73% of #supplychain tweets

contained two or more hashtags Factors for information diffusion

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Discussion...(Topics)

Dennis L. Kappen Twitter :3d_ideationImage Source: http://blog.mytmc.com/wp-content/uploads/2015/01/ConnectPorts.jpg

Topic Areas Popular hashtags Topics of interest

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Discussion...(Users)


Image Source: http://http://erau.edu/-/media/images/shared/degrees/videos/worldwide/master-of-science-in-logistics-and-supply-chain-management-source.png

Characteristics of users Job or career services SCM practitioners Trade magazines

Active users vs Visible users Users vs Tweets

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Discussion...(Sentiments)


Image Sourcehttp://beta.www.hull.ac.uk/editor-assets/images/Logistics/supply.png

#supplychain had low sentiment Major events influencing sentiments Promotional tweets Negative sentiment

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Implications


Image Sourcehttp://beta.www.hull.ac.uk/editor-assets/images/Logistics/supply.png

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Limitations and Future Work


Short data collection period #supplychain vs keywords Future work

Guidelines Impact of social media on supply chain

performance

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Challenges (IMHO)


Research Methods section Reporting Results Themes in word analysis and

sentiment analysis No explanation of the evolution of

these themes (inductive or deductive ?)


www.gamefulplay.caTwitter :3d_ideation.co

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Thank You

Date post:	15-Apr-2017
Category:	Data & Analytics
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#supplychain and Twitter Analytics

Data & Analytics