{"title":"Features to Improve The Interactivity of Government’s Post on Social Media","authors":"CS. Purwowidhu Widayanti, Irwansyah","doi":"10.1109/ICACSIS47736.2019.8979782","DOIUrl":null,"url":null,"abstract":"This study elaborates measurements of interactivity on social media as well as describes the predictors that can strengthen the interactivity of government’s post on Facebook and Twitter account. A content analysis was conducted on 143 posts and 313 tweets over one of government’s official account. The result shows a significant predictor of interactivity from content features both on Facebook and Twitter is the topic of posts or tweets. The topic that generally has a positive influence on the overall type of interactivity and breadth of interactivity both on Facebook and Twitter is the topic of public service advertising. A significant predictor of interactivity from the structural features on Facebook is the hashtag while significant predictors of interactivity from structural features on Twitter are multimedia elements and external links.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACSIS47736.2019.8979782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study elaborates measurements of interactivity on social media as well as describes the predictors that can strengthen the interactivity of government’s post on Facebook and Twitter account. A content analysis was conducted on 143 posts and 313 tweets over one of government’s official account. The result shows a significant predictor of interactivity from content features both on Facebook and Twitter is the topic of posts or tweets. The topic that generally has a positive influence on the overall type of interactivity and breadth of interactivity both on Facebook and Twitter is the topic of public service advertising. A significant predictor of interactivity from the structural features on Facebook is the hashtag while significant predictors of interactivity from structural features on Twitter are multimedia elements and external links.