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Discovery of Twitter User Interestingness Based on Retweets, Reply Mentions and Pure Mentions Relationships

Ong Kok Chien , Poo Kuan Hoong and Chiung Ching HoFaculty of Computing Informatics, Multimedia University Cyberjaya.

2016 International Conference on Information in Business and Technology Management (I2BM)

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2016 International Conference on Information in Business and Technology Management (I2BM)

Outline

IntroductionObjectiveMethodsResultsSummary

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2016 International Conference on Information in Business and Technology Management (I2BM)

Introduction

Explore the graph relationships between Retweets (RT), Reply-Mentions, (RM) and Pure-Mentions (PM)

Compare the ranking with hand-marked (HM) ranking by seven (7) annotators

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2016 International Conference on Information in Business and Technology Management (I2BM)

Twitter

Maximum 140 characters microblogging site.

“A Tweet is an expression of a moment or idea. It can contain text, photos, and videos. Millions of Tweets are shared in real time, every day.”

Reply

Retweet

Favorite

Hashtags

https://about.twitter.com/what-is-twitter/story-of-a-tweet

.com

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2016 International Conference on Information in Business and Technology Management (I2BM)

Objectives To rank Twitter users using Page Rank.

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2016 International Conference on Information in Business and Technology Management (I2BM)

Methods

Link-based ranking algorithms (PageRank)

Twitter Users as Nodes.

Relationships as Edges.

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2016 International Conference on Information in Business and Technology Management (I2BM)

Example

PageRank (PR) E.g.: BackLinks in Websites - Referring back to

Original Content.

- Sergey Brin & Larry Page (1998). The anatomy of a large-scale hypertextual Web search engine.

Image extracted from Wikipedia

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2016 International Conference on Information in Business and Technology Management (I2BM)

Example

Minister of Youth & Sports

Khairykj

shatyrah2

AyenSanji

RT-ed RT-ed

https://twitter.com/Khairykj/status/410964119521460224

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2016 International Conference on Information in Business and Technology Management (I2BM)

Architecture

Twitter Streaming API

Configure Keywords

1 JSON raw data2

3 HiveQL 4 UnixScript

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2016 International Conference on Information in Business and Technology Management (I2BM)

Keywords

HyppTV Streamyx UMobile Unifi Yes4G Celcom xpaxsays

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2016 International Conference on Information in Business and Technology Management (I2BM)

Basic Statistics

Dataset Total Tweets : 7,931 After discard non-native Retweets: 7,922 English Tweets (language=en): 2,229 Unique RT pairs of users: 512 Unique PM pairs of users: 620 Unique RM pairs of users: 545 Unique Full-Mention (FM) pairs of users: 1,154

1st Feb 2015 -> 7th Feb 2015

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2016 International Conference on Information in Business and Technology Management (I2BM)

Categories of Tweets

Tweets are categorized into the following categories: (1) News - products/company info; (2) Advertisements - promotion; (3) Business - special offers; (4) Jokes - funny/pranks content; (5) Questions - seeking for answers/response; (6) Answers - response to a question (@mentions); (7) Statement - Complaints/comments/feedback; (8) Conversation - response to another tweets; and (9) Irrelevant - not related to telco products/services.

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2016 International Conference on Information in Business and Technology Management (I2BM)

Interestingness score schema

The interestingness score schema was set from the range 0 to 4: 0 = Irrelevant; 1 = Less Interesting/Informative; 2 = Interesting/Informative; 3 = Quite Interesting/Informative; and 4 = Very Interesting/Informative

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2016 International Conference on Information in Business and Technology Management (I2BM)

Results Scored an average informative/interestingness score

of 1.33 out of 4 by our 7 annotators from 2 iterations. Agreement amongst 7 annotators after 2 iterations

for 9 categories was 62.27% and score (between 0-4) was 51.64%.

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2016 International Conference on Information in Business and Technology Management (I2BM)

Results

Rank

HM RM PM FM RT

1 Asianadotmy

Azwnrafi Zaynneutron Zaynneutron

Zaynneutron

2 Zulhusnia Lauravinzant

Shahril_Wokay2

Ndiarzali88 Ndiarzali88

3 IzRijap TuneTalk Azwnrafi TuneTalk UniFiEdge4 Socasnov FirdausAzil TuneTalk Lauravinza

ntTuneTalk

5 Pjolll Alliebnormand

Alliebnormand

Azwnrafi Asianadotmy

6 uk_htc FookHeng_Lee

Twtwanitaa FirdausAzil uk_htc

7 FookHeng_Lee

Pjolll Lauravinzant FookHeng_Lee

HyppWorld

8 TuneTalk Ndiarzali88 FirdausAzil Twtwanitaa Zulhusnia9 NurIllihazwa

niUniFiEdge FookHeng_L

eePjolll IzRijap

10 Shahril_Wokay2

HyppWorld Pjolll Alliebnormand

FookHeng_Lee

• RT shows the closest match of ranking sequence as compared to RM and PM.

• For the case of RM and PM, RM appears to be a better match to the HM sequence.

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2016 International Conference on Information in Business and Technology Management (I2BM)

SummaryA PR graph relationships analysis of how RT, RM and PM impact the perception of user-level informative/interestingness, validated with HM evaluations.

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2016 International Conference on Information in Business and Technology Management (I2BM)

Future Work

Further evaluation to be conducted using different weightages of RT, RM and PM.