PurposeAn optimal timing for diagnosis and management of papillary thyroid microcarcinoma (PTMC) has become the subject for much controversy. The aim of the present study is to analyze people's preference in Korea for timing of diagnosis and management of PTMC using an online questionnaire.MethodsThe questionnaire consists of 3 questions about preference for the diagnosis and management of PTMC and 3 additional questions about respondents' personal information. An online survey was conducted from March 3 to June 3 in 2015 using Google Survey (http://goo.gl/forms/b81yEjqNUA).ResultsA total 2,308 persons (1,246 males, 1,053 females) answered the questionnaire. Respondents' ages varied widely from teenagers to 70-year-olds. If there was a suspicious thyroid nodule from PTMC measuring less than 1 cm in diameter, 95.7% of respondents want to know a cytological diagnosis for it. If a thyroid nodule turned out to be a PTMC, 59.5% of respondents wanted it removed immediately. For surgical management of PTMC, 53.0% of respondents were worried more about recurrences than complications. In subgroup analyses, respondents younger than 40 years old more often want immediate surgery than others: 66.7% vs. 32.7% (P < 0.05). Respondents who underwent thyroid cancer surgery (n = 91) were worried more about recurrences than others: 69.2% vs. 52.4% (P < 0.05).ConclusionAlmost all respondents in the present study wanted diagnosis of suspicious thyroid nodules immediately. However, there were opposing opinions about the preferred timing for surgical treatment and surgical extents. A patient's right to know their disease status and decision on treatments should be emphasized all the more.

Recently, interests in detecting hot topics have been significantly growing as it becomes important to find out and analyze meaningful information from the large amount of data which flows in from social network services. Since it deals with a number of random writings that are not confirmed in advance due to the characteristics of SNS, there is a problem that the reliability of the results declines when hot topics are predicted from the writings. To solve such a problem, this paper proposes a high reliable hot topic prediction scheme considering user influences in social networks. The proposed scheme extracts a set of keywords with hot issues instantly through the modified TF-IDF algorithm based on Twitter. It improves the reliability of the results of hot topic prediction by giving weights of user influences to the tweets. To show the superiority of the proposed scheme, we compare it with the existing scheme through performance evaluation. Our experimental results show that our proposed method has improved precision and recall compared to the existing method.■ keyword :|Social Network Services|Twitter|Hot Topics|Prediction|

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