The world’s libraries. Connected. “How much change do you get from 40$?”

The world’s libraries. Connected.

“How much change do you get from 40$?”


“What is Warm Mix Asphalt?”


“What color are your underwear?”


Analyzing and Addressing Failed Questions on Social Q&A

Chirag Shah, Marie Radford, Lynn Connaway,

Erik Choi, & Vanessa Kitzie


The Background

BACKGROUND1. Online question-answering (Q&A) services are becoming increasingly popular among information seekers. (Yahoo Answers, WikiAnswers, Google Answers, Quora, etc)

HOWEVER..

2. There is no guarantee that the question will be answered.3. The large volume of content on some of SQA sites renders participants unable to answer the questions

4. Some questions may be suitable in QA site A while

others may be more suitable in QA site B


The Goal

GOAL1. Analyzing why some questions on social Q&A sites are failed

2. Developing a typology of failures for questions

3. Since Q&A services encompass social Q&A (SQA) and

virtual reference service (VRS), the study attempts to

analyze some failed questions from SQA, and propose

how SQA including the questions could be restructured

or redirected by VRS


Information seeking questions

The study focuses on only "failed information seeking questions"

1. Advice and opinion seeking questions (e.g., Is

happiness a choice?) are hard to answer

2. Previous research argue that SQA generate more conversational questions; VRS generate more informational questions.

3. A focus of bridging Q&A services (SQA + VRS)

- Suggesting the features of VRS to failed Qs on SQA


Data Collection

Using the Yahoo! Search API (Application

Programming Interface) to collect unresolved

questions from November 2011 to March 2012

- 13,867 such questions were collected

- The remaining 4,638 (about 33%) questions were those with zero answers, and thus were considered to have “failed”

- Identifying 200 (about 5%) failed information seeking questions


Data Analysis

- Using a grounded theory (Glaser & Strauss, 1967)

- Two coders analyzed data and constructed a typology of

failed information seeking questions. (ICR - 90.50%)

- Coders agreed that some questions have minor attributes for failures


Data Analysis

Typology of failed information seeking questions

1. Unclear - Ambiguity - Lack of information - Poor syntax

2. Complex - Too complex and/or overly broad - Excessive information

3. Inappropriate - Socially Awkward - Prank - Sloths

4. Multi-questions - Related questions - Un-related questions


Data Analysis

RESULTS


Finding

The first significant proportion of the failed questions: too complex and/or overly broad (n=68)

“What were the effects of slavery as an institution in

Frederick Douglas Narrative of the life of frederick

dou?”

- A lack of perceived effort on the asker’s part to craft a

coherent question may cause difficulties in its

subsequent interpretation - Questions from this category involve topics too complex and/or specialized, which few people could address. - Sometimes, they are too specific place/people focused.


Finding

The second most significant attribute of failure: lack of information (n=28)

“How much would transmission swap cost?”

- Inadequate information increases the chance of potential respondents misinterpreting the asker’s intent.

- Questions lacking information often discourage responses as they can be perceived by potential

respondents as being too complicated to address.


Finding

The third significant attribute of failed questions: multiple related questions are assigned in one body of a question (26, 13%)

Title: “What is Warm Mix Asphalt? Q1 Content: “I recently ….. could be placed and made at a lower temperature. How long has industry been using this product successfully? Q2 Does it last as long as new pavement that is placed at higher temperature and contains less receycled material?Q3


Finding

The third significant attribute of failed questions: multiple related questions are assigned in one body of a question (26, 13%)

- Asking more than one question simultaneously distracts people to respond, since they must address each question and attempt to translate all of the questions into a single information need

- Even if all of the questions are somehow related and

intended to provide enough information to explicate the

asker’s information need, multiple questions may

conversely impair the understanding.


Finding

The last significant proportion of the failed questions: ambiguity (n=21)

“How much change do you get from 40$?”

- Questions that are too vague or too broad may cause misunderstanding regarding their meaning and/or foster multiple interpretations

- Lack of a coherent and/or clear manifestation of the asker’s information needs discourages responses as people’s murky understanding of what the asker is looking for


Conclusion

1.Identifying why questions fail could be the first step toward helping information seekers revise their questions.

2.Since there is little in the literature addressing failed questions in VRS or SQA, this typology could be used to better understand why some questions fail.

3.Testing the typology presented here could help experts(librarians) better assist end-users by identifying when it isappropriate and how to clarify questions


Possible applications

1. Employing VRS techniques

- Librarians in face-to-face and virtual environments rely on a process of clarifying or negotiating the reference question (Ross, Nilsen, & Radford, 2009) in order to translate the user’s initial statement of an information need into a strong research query that returns relevant results.

- This process of 'negotiation' is largely absent in SQA, so this findings suggest "modification" would help to compensate for this absence, or, minimally, provide feedback to allow the user to construct (or reconstruct) a better question.


Possible applications

2. Incorporating relevance feedback within the SQA platform.

- Relevance feedback represents a self-directed “question negotiation”

- Helping to identify pertinent elements to addressing his/her information need

- Providing the user with feedback of how to reformulate his/her question (using the coding scheme developed in the study)


Funding & Acknowledgements

Cyber Synergy: Seeking Sustainability through Collaboration between Virtual Reference and Social Q&A Sites

$250,000 for 2011-2013Funded by IMLS, OCLC, & Rutgers UniversityCo-PIs Marie Radford (RU), Lynn Silipigni Connaway (OCLC), & Chirag Shah (RU)

http://www.oclc.org/research/activities/synergy.html

http://www.oclc.org/research/activities/synergy.html


Questions?

• The paper is submitted to ASIST 2012• Co-authorship: Erik Choi, Chirag Shah,Marie Radford, Lynn Connaway,

and Vanessa Kitzie

Documents

The world’s libraries. Connected. “How much change do you get from 40$?”