Social Query: A Query Routing System for Twitter

Social Query A Query Routing System for Twitter

Cleyton Souza Jonathas Magalhães, Evandro Costa, and Joseana Fechine

Laboratory of Artificial Intelligence – LIA

Federal University of Campina Grande - UFCG

Introduction

• Query Routing (QR) is the process of directing questions to appropriate responders

– Community Question and Answering Services (CQA)

– Online Social Networks (OSN)

• We are proposing an Expertise Finding System to automatically routing questions on Social Networks

Cleyton Souza - ICIW 2013 2

Introduction

• Our goal is to present the Social Query System • How does it work?

• How does the usual Q&A process is affected?

• Talk about our preliminary results

• Talk about our planning for the future


Agenda

• Introduction

• Related Work & Background

• Usual Q&A

• Social Query System: How it works

• Evaluation & Results

• Future Work


Related Work & Background

• The differential of our research

– We are proposing a Query Routing to an OSN context

• Previous work usually focused on CQA context

• We are proposing a solution to a pre-existent and popular context: Twitter

• Most part of questions asked on Twitter are not answered (more than 80%) [Paul et al. 2012]

– We lead with the recommendation as multi-criteria decision making problem

• Previous work usually apply probabilistic or Information Retrieval-based models;


Usual Q&A on OSN

• Sharing a public question

Fig. 1: Sharing a Public Question


Q&A on OSN

• Directing the question

Fig. 2: Directing the Question


Q&A on OSN

• Routing the question

Fig. 3: Routing the Question


Social Query System

• Works outside Twitter

– Questioner’s Followers are Expert Candidates

– Questions and Answers without size limitations

Fig. 4: Social Query System’s Homepage Cleyton Souza - ICIW 2013 9

“New Question” Page

• Three text fields, two mandatory

Fig. 5: “New Question” Page Cleyton Souza - ICIW 2013 10

“Recommendation List” Page

• Questioner chooses who will “receive” the question

Fig. 6: “Recommendation List” Page


Question’s Tweet

• Questioner tweets the following message

Fig. 7: Question’s Tweet


“New Answer” Page

• Three options of answer

Fig. 8: “New Answer” Page Cleyton Souza - ICIW 2013 13

“I don’t Know” & “I know Someone”

Fig. 9: “I don’t know” Tweet

Fig. 10: “I know someone” Tweet


I want answer

• When the expert clicks on the “I want answer” button

Fig. 11: “I want answer” Page Cleyton Souza - ICIW 2013 15

Tweeting about the Answer

Fig. 12: “I just answered” Tweet


“New Evaluation” Page

Fig. 12: “New Evaluation” `Page


How does it work?

• (1) The questioner accesses our System and (2) informs his question;

• (3) The System recommends potential responders and (4) the questioner chooses to whom direct the question;

• (5) Those chosen access our System, (6) answers the question, (7) and informs the questioner about his answer;

• (8) The questioner access our System, (9) see the answer, and (10) evaluates it.


Evaluation

• Nine Volunteers evaluated ten recommendations for a couple of questions

a) Looking for a new band to listen during weekend, does anyone have an indication?

b) Going to the movie theater after years LOL. What is the best movie in theaters?

• Each recommendation was labeled as good (relevance 1), neutral (relevance 0) and bad (relevance 0).

• These labels reflect the opinion of the volunteers about the recommendation


Results

Cases Amount of Followers

% of good %of bad nDCG

Best case for Question “a” 192 50% 10% 0.63

Worst case for Question “a” 129 30% 60% 0.25

Best case for Question “b” 121 60% 0% 0.74

Worst case for Question “b” 68 30% 0% 0.18

Average for Question “a” 110 41% 28% 0.41

Average for Question “b” 110 50% 20% 0.51


Future Work

• Where are we?

• Mobile App

• Volunteer’s feedback

– Follow Back Filter

– Thesaurus

• Real case study


Social Query System A System for Query Routing on Twitter

Cleyton Souza Jonathas Magalhães, Evandro Costa, and Joseana Fechine

Laboratory of Artificial Intelligence – LIA

Federal University of Campina Grande - UFCG

Thank You!

Lia TIPS Laboratory of Artificial

Intelligence Group of Intelligent Social and

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Social Query: A Query Routing System for Twitter

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