分析結果顯示：(1) 假期結束前的晚上，包括週末在內，與負面情緒相關的Hashtag達到高峰。假期後症候群 (Post-holiday syndrome)，即藍色星期一 (Blue Monday) 確實存在。使用者在假期晚上結果更高，這代表這個現象是從前一天就已開始，並蔓延到隔天。(2) 在正常工作日時，中午之前的Hashtag數量是最低的。表示大多數人都正常地休息，並且不會在工作開始之前進行抱怨。(3) 工作日的下午是數量第二低的時段，這表示雖然利用行動裝置使用社群媒體十分方便，但大部分員工不會使用上班時間來接觸社群網絡。(4) 數量第二高的是工作日的晚上，表示經過一整天的辛勤工作，使用者心情疲憊，並且有時間發洩抱怨。(5) Hashtag的分析實際上可以作為反應使用者情感的方法。;The last two decades has witnessed a tremendous advance in both Internet and mobile network usage. On the social network front, younger generation more often choose to use Instagram, rather than Facebook. Many people express their emotions on Instagram using hashtags. In recent year, job stress has always been a public concern.
This study attempts to explore the phenomena of Instagram users expressing negative emotions, including stress and occupational burnout on the Instagram. A content analysis was carried out, analyzing Hashtags relating to stress and burnout. Data from 5204 post using Hashtag were collected and analyzed SPSS. The data was also cluster analyzed.
Analysis reveals that: (1) Hashtag phonation related to negative emotions peaks during the evening before closing of a holiday, including weekends. Post-holiday syndrome (i.e. Blue Monday) truly exist, and users are even bluer on holiday evenings, meaning it actually starts the night before. (2) Hashtag phonation during the wee hours and the morning (before noon) on normal work days is the lowest, indicating most people do rest normally, and do not tend to complain when they start working. (3) The afternoons of work days is the second most silent period. Together with workday morning just mentioned, these show that while the use of social networks on smartphones are convenient, employees still refrain from using employer’s time to access social networks. (4) The second highest phonation level goes to workday evenings, indicating that after a whole day of hard work, users are tired with their body and mind, bad mood surge and it is free time to express their complains. (5) Analysis of Hashtags can actually be used as an expedient way of reflecting user emotions.
