Social Network Analysis: Type of Information and Characteristics of Its Delivery Regarding Helicobacter pylori in Korea

Bang, Chang Seok; Baik, Gwang Ho

Abstract

BACKGROUND/AIMS
Current production of knowledge and distribution of data is frequently mediated by social media in the form of unstructured text data rather than classical newspaper or journal format. Management of Helicobacter pylori infection is an important issue in Korea. However, there has been no study on the characteristics of information regarding H. pylori consumed and distributed in the social media by general population.
MATERIALS AND METHODS
This study evaluated characteristics of social media data regarding H. pylori in Korea using semantic network analysis with Textom and NodeXL Pro (2015.8.11~2016.8.11, Naver, Daum, Youtube, and Twitter searching).
RESULTS
Total collected data in the Textom analysis about "˜í—¬ë¦¬ì½”ë°•í„°' was 10,061. TF-IDF (term frequency Ã— inverse document frequency) was as follows: "˜ìœ„ì•”', "˜ìœ„', "˜ê°ì—¼', "˜ìœŒ', "˜ê· ', "˜ì¹˜ë£Œ', "˜ìœ„ê¶¤ì–‘', "˜ì›ì¸', "˜í”„ë¡œì íŠ¸', "˜ìŒì‹', "˜ì„¸ê· ', "˜ê²€ì‚¬', "˜ì˜ˆë°©', "˜ì¦ìƒ', "˜ê±´ê°•', "˜ì•½', "˜íš¨ê³¼'. In the Twitter analysis, 96 nodes and 120 edges, and 86 unique edges were detected, suggesting low distribution of data. Misinformed data such as "˜í—¬ë¦¬ì½”ë°•í„°-íŒŒì´ë¡œë¦¬', "˜ë¼ëŠ”-ë°”ì´ëŸ¬ìŠ¤ë•Œë¬¸ì—', "˜í—¬ë¦¬ì½”ë°•í„°-í”„ë¡œì íŠ¸', "˜ìœ„ê¶¤ì–‘ì´ë‚˜-ìœ„', "˜ì ë§‰-ì¶œí˜ˆì„', "˜ë¹„ë¡¯í•˜ì—¬-ê°ì¢…', "˜ë¶€ì¢…ì„-ì–µì œí•˜ê³ ', "˜ì¹˜ë£Œí•˜ëŠ”ë°-íš¨ê³¼ê°€', "˜ìžˆìŠµë‹ˆë‹¤-ë˜í•œ', "˜ìž¥í‹°í‘¸ìŠ¤-ì´ì§ˆ', "˜ë“±-ì „ì—¼ì„±', "˜ì„¸ê· ì´ë‚˜-ìž¥', "˜ì†ì˜-ì„¸ê· ë“¤ì„', "˜ì–µì œí•˜ëŠ”-íš¨ê³¼ê°€', "˜í”„ë¡œì íŠ¸-ìœŒ' were found. The most viewed movie in the Youtube analysis was "˜í•œêµì•¼ì¿ ë¥´íŠ¸í—¬ë¦¬ì½”ë°•í„°í”„ë¡œì íŠ¸ìœŒê·¸í•œìž…ì„ê²½ê³„í•˜ë¼_15ì´ˆ' (210,577).
CONCLUSIONS
Relative insufficiency, low distribution, and some misinformed data were found in some part of social media. Participation of healthcare professional is warranted to solve these issues.