(1) Accuracy

a. Convincing: factual information contains in the answer, if any, looks to be both valid and reliable. If used any references, the sources are credible. (Jeon, Kim, & Chen, 2010)
b. Relevant: the answer is not off-track. The answer is highly relevant to the question. (Jeon et al., 2010)
c. Complete: this answer completely answers the whole question (rather than a part of it). (Shah & Pomerantz, 2010)
d. Objective: the answer provided is impartial. (Shah & Pomerantz, 2010)

(2) Interestingness and readability

a. Intriguing: the answerer attempts to give an answer out of boredom or mischief. (Chen & Sin, 2013)
b. Understandable: the pertinence of information, and understandability of answer is high. (Jeon et al., 2010)
c. Clarity: the answerer attempts to enhance his or her answer’s clarity, comprehension and retention and thereby be deemed effective by a wider audience. (Ghose & Ipeirotis, 2011)
d. Logic: the logic of the answer is easy to follow. (Shah & Pomerantz, 2010)
e. Polite: the answer is polite (not offending).(Shah & Pomerantz, 2010)

(3) Richness

a. Detailed: there are sufficient details with expanded explanations offered by the answer to serves as a proxy for answer effectiveness. (Jeon et al., 2006)
b. Diversified: There is a clear evidence that the answerer attempted to illustrate his or her answer in a diversified manner. (Jeon et al., 2006)

(4) Usefulness

a. Practical: the knowledge contained in the answer is highly practical and easy to use. (Shah & Pomerantz, 2010)
b. Helpful: this answer is useful or helpful to address the question. (Shah & Pomerantz, 2010)

Chen, X., & Sin, S. C. J. (2013). ‘Misinformation? What of it?’Motivations and individual differences in misinformation sharing on social media. Proceedings of the Association for Information Science and Technology, 50(1), 1-4.
Ghose, A., & Ipeirotis, P. G. (2011). Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498-1512.
Jeon, G. Y., Kim, Y.-M., & Chen, Y. (2010). Re-examining price as a predictor of answer quality in an online Q&A site. Paper presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.
Shah, C., & Pomerantz, J. (2010). Evaluating and predicting answer quality in community QA. Paper presented at the Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval.