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Future Internet 2018, 10, 77 5 of 12 myself”, “To depict my life through photos”) [35,53]. In addition to these four question items, we also added “To record my emotional state (innermost feelings)”. Factor 3: Diversion was proposed by [56] and defined as “escape from boredom or problems, and emotional release”. It contained five items (e.g., “To relax”, “To avoid loneliness”, “To escape from reality”) [35]. We further added “To kill time” and “To escape awkward situations (pretending to be busy or in traffic)”. Factor 4: Self-Promotion is a feeling [35,57]; psychologists posit that people promote themselves using personalized new technology to pursue fame and feel valued [58]. It contained five items (e.g., “To become popular”, “To show off”, “To self-promote myself”) [53]. We further added “To gain attention from followers (comments and likes)”. Pets make most people happy, and many people are willing to share pictures of their beloved pets. Instagram has become a platform for pet lovers, where many people show off their pets (mainly cats and dogs) in various environments [59]. Thus, we also added “To show off my pet”. Factor 5: It is creativity. Mull & Lee [34] found that creativity is one of the motives for Pinterest use. We define creativity as “the ability to cultivate and express” It contained six items, including “To create art” and “To show off my photography skills”, which were proposed by [35]. As some of the participants of this study were design majors, we added four other question items: “To appreciate different lifestyles and photography works”, “To seek creative inspiration (such as strange and unique things and cultural and creative designs)”, “To look at current fashion brand trends”, and “To look at current fashion wear and outfits”. We used the 27 items and 5 factors above to understand participant motives for Instagram use. 3.2. Sample Description & Structure of Questionnaire A revised version of the motive scale developed by Sheldon et al. [53] was conducted online. We targeted the questionnaire at Instagram users who were undergraduates and postgraduates majoring in design or engineering in Taiwan. This study employed the uses and gratifications theory to explore the roles played by satisfaction effects resulting from the Instagram use of young adults. A structured online questionnaire was then used to understand the usage behavior involving this social media app. The structure of the questionnaire comprised three parts. The first part contained a survey of the topics that the participants followed and were interested in and their attitudes towards ads on Instagram. The second part was divided into two parts regarding the motives of participants for looking at and creating Instagram posts using the 27 question items above. The question items were measured on a five-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement. The participants were asked to respond based on their personal habits and feelings. The total score and mean score of each factor were used to represent the intensity of each respondent’s relevant traits. In the third part, the participants were asked to provide personal information. 4. Results The questionnaire was administered from 3 October to 27 October in 2017. On average, it took participants 7 min to finish the questionnaire. In the end, we obtained a total of 307 valid questionnaires from university design or engineering majors that had Instagram accounts and were in their second year or higher. The participants included 133 male students and 174 female students; 172 participants were design majors, and 135 were engineering majors. In terms of the amount of time spent on Instagram every day, 178 participants spent less than 1 h, 99 participants spent between 1 h and 3 h, and 30 participants spent more than 3 h. The reliability and validity analyses of the questionnaire were as follows. We adopted factor analysis to categorize the problem attributes of the questionnaire content. A Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity produced KMO = 0.859 and p = 0.000, which reached the level of significance and thus indicated that factor analysis was appropriate. Further reliability analysis of the problem attributes revealed Cronbach’s α values between 0.901 and 0.907; overall reliability was 0.907, which met the basic requirement of a Cronbach’s α value greater than 0.7. Thus, our questionnaire had decent consistency and stability.PDF Image | PageRank algorithm with MPC
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