3. Methodology
4.2. Factor Analysis
Descriptive for emotional outcomes of Instagram Stories use (N = 296)
Variable M SD
Emotions (α = .88) 3.12 0.88
Positive emotions (α = .91) 4.12 1.21
Joy (happy, pleased, joyful) 4.65 1.44
Contentment (contented, fulfilled) 4.52 1.53 Optimism (optimistic, encouraged, hopeful) 4.51 1.48
Peacefulness (calm, peaceful) 4.42 1.52
Excitement (excited, thrilled, enthusiastic) 4.41 1.53 Surprise (surprised, amazed, astonished) 4.12 1.55 Love (loving, sentimental, warm hearted) 3.56 1.69 Romantic love (sexy, romantic, passionate) 2.75 1.68
Negative emotions (α = .93) 2.13 1.12
Envy (envious, jealous) 2.85 1.68
Loneliness (lonely, homesick) 2.39 1.49
Discontent (unfulfilled, discounted) 2.14 1.33
Worry (nervous, worried, tense) 2.08 1.36
Sadness (depressed, sad, miserable) 2.07 1.33 Anger (frustrated, angry, irritated) 1.92 1.21 Shame (embarrassed, ashamed, humiliated) 1.80 1.26
Fear (scared, afraid, panicky) 1.76 1.27
Apart from emotional outcomes, social media dependency is another
psychological consequences of Instagram Stories use examined in this study. While participants showed they were indeed reliant on Instagram Stories (M = 3.17, SD = 1.36), the mean score of mood regulation (M = 3.77, SD = 1.70) was higher than cognitive preoccupation (M = 3.23, SD = 1.54) and compulsive Internet use (M = 2.64, SD = 1.49). Specifically, participants were more likely to use Instagram Stories to manage their moods (see Table 10).
Table 10
Descriptive for Social Media Dependency (N = 296)
Variable M SD
Social Media Dependency (α = .94) 3.17 1.36
mood regulation 3.77 1.70
cognitive preoccupation 3.23 1.54
compulsive Internet use 2.64 1.49
4.2. Factor Analysis
To answer RQ1 that investigates Millennials’ motivations for using Instagram Stories, an exploratory factor analysis (EFA) based on the principal component extraction with varimax rotation was performed to identify specific motivations for
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Instagram Stories use (Lee et al., 2015; Mull & Lee, 2014; Punyanunt-Carter et al., 2017; Sheldon & Bryant, 2016). Principal component analysis (PCA) is a cluster analytical technique for identifying groups or clusters of variables, and it is used to condense the data set into a more convenient and manageable size while retaining as much of the original information as possible (Field, 2005). Through the PCA, each item had an equal chance to cluster to any one of the factors (Morecroft, Cantrill, &
Tully, 2006). Meanwhile, one of the orthogonal rotation, varimax, was used to maximize the dispersion of factor loadings (Field, 2005). Accordingly, an eigenvalue greater than or equal to 1.0 and a loading score for each factor greater than or equal to 0.40 were required to retain a factor (Nunnally, 1978).
The initial EFA consisted of 38 items suggested that eight factors should be retained; however, since the item “Because I enjoy editing stories with the features (e.g., filters, texts, emojis)” had no loadings, the item was eliminated. As a
consequence, the PCA results showed that the eight-factor, 38-item measure accounted for 66.97% of the total variance explained. The obtained factors were named based on the U&G literature (e.g., Whiting & Williams, 2013) and the
meanings of the items. Eight factors were defined as: exploration, recognition-seeking, perceived functionality, entertainment, social sharing, interaction, novelty, and
surveillance (see Table 11).
Factor 1, labeled “exploration” (eigenvalue = 12.27), contained nine items (e.g., “To interact with brands,” “To browse products/services (e.g., clothes, shoes),”
“To buy products/services (e.g., clothes, shoes),” “To explore,” “To get free
information without much effort,” “To learn about new things (e.g., watching tutorials, etc.),” “To keep up with current issues and events of the day,” “To receive exclusive contents in real time,” and “To receive exclusive contents in real time”) and accounted for 32.30% of the total variance after rotation (α = .90). Mull and Lee (2014) found that users use Pinterest for virtual exploration (i.e., exploring images for interesting ideas and learning), which is similar to McQuail’s (1983) motivational dimension of information seeking, yet both of the identified motivations are merely about
information searching and learning. Nevertheless, taken in Instagram Stories context, users not only exploring exclusive information but also interacting with brands and making purchases.
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Factor 2, “recognition seeking” (eigenvalue = 4.10), explained 10.80% of the variance (α = .84), and consisted of four items (e.g., “To create my own portfolio (e.g., vlogging),” “To self-promote,” “To become popular,” and “To show off”). Since imagery presentation of personalities, lifestyles, and tastes on Instagram empowers users’ impression management (Lee et al., 2015), gaining replies (e.g., “likes” or emoji reactions) and having a considerable number of viewers help validate popularity and status among peers on Instagram (Sheldon & Bryant, 2016), and satisfy the psychological needs to be seen and valued (Greenwood, 2013). As a result, this factor was named “recognition seeking” following the terminology used in prior research (Chen, 2018; Shao, 2009).
Factor 3, “perceived functionality” (eigenvalue = 2.22), accounted for 5.83%
of the variance (α = .86) and included five items (e.g., “Because it is easy to use,”
“Because it is casual,” “Because it is functional,” “Because it is convenient,” and
“Because it is real”). This factor is closely related to Whiting and Williams’s (2013) convenience utility of social media use as it illustrates perceived usefulness and perceived ease of use of Instagram (Hwang & Cho, 2018) and implies the functional dimension of social media. However, unlike some studies only focusing on SNS usability and functionality (Korhan & Ersoy, 2016), this factor also reflects the specific perceptions of Instagram Stories due to its fast and visual nature: casualness and realness. Therefore, this factor was named “perceived functionality.”
Factor 4 was named “entertainment” (eigenvalue = 1.84), and explained 4.84% of the variance (α = .85), containing four items (e.g., “To pass the time when bored,” “Because it is entertaining,” “Because it is enjoyable,” and “Because it is fun”). This factor is supported by the literature in that SNSs usually help satisfy users’
needs for entertainment (Mull & Lee, 2014; Whiting & Williams, 2013).
Factor 5, “social sharing” (eigenvalue = 1.55), accounted for 4.07% of variance (α = .83) and comprised seven items (e.g., “To share information about me (e.g., feelings, updates, etc.),” “To share information I think is interesting (e.g., reposting),” “To promote certain topics,” “To see what other people share,” “To record things that happen in my daily life,” “To receive responses from others,” and
“To feel like I belong to a community”). This factor is associated with Whiting and Williams’s (2013) concept of information sharing with others and expression of opinion, but it also contains the dynamic social aspect as users want to see what others
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share and receive others’ responses. As the literature suggests, individuals use SNSs for self-presentation, for feeling included, and for fulfilling their need to belong (Nadkarni & Hofmann, 2012). Therefore, this factor was named “social sharing.”
Factor 6, “interaction” (eigenvalue = 1.35), accounted for 3.55% of variance (α = .75) and embodied four items (e.g., “To have conversations with others (e.g., chats, gossip, etc.),” “To maintain a good relationship with others (for networking),”
“To meet/connect with others who have similar interests,” and “Because I can receive some benefits (e.g., giveaways, coupons).” The theme of this factor is communicating and interacting with others as well as maintaining relationships with others, which has been supported by previous U&G research relating to social media use (Alhabash &
Ma, 2017; Lee et al., 2015).
Factor 7, “novelty” (eigenvalue = 1.09), explained 2.86% of the variance (α
= .73) and included three items (e.g., “Because it is private,” “Because it is new,” and
“Because it disappears after 24 hours”). This factor was originally proposed by Sundar and Limperos (2013) and defined as seeking unusual experience of accessing technology with different interface that is new and innovative.
Finally, Factor 8, “surveillance” (eigenvalue = 1.03) with two items (e.g., “To keep in touch with family and friends” and “To get updates on my family and
friends”), accounted for 2.71% of the variance (r = .59). Initially proposed by Whiting and Williams (2013) and further specified by Sheldon and Bryant (2016),
“surveillance” is defined as watching what other people are doing. However, in this study, surveillance is more about keeping in touch with close ties (i.e., family and friends). Table 11 summarizes the item wording for each motive.
Table 11
Summary of Exploratory Factor Analysis Results for Motivations (N = 296)
Factor title, indicator, and item EFA Loading
Factor 1: Exploration (α = .90)
To interact with brands. .66
To browse products/services (e.g., clothes, shoes). .74
To buy products/services (e.g., clothes, shoes). .56
To explore. .65
To get free information without much effort. .67
To learn about new things (e.g., watching tutorials, etc.). .71 To keep up with current issues and events of the day. .64
To receive exclusive contents in real time. .60
To follow influencers/celebrities. .63
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Factor2: Recognition Seeking (α = .84)
To create my own portfolio (e.g., vlogging). .52
To self-promote. .75
To become popular. .82
Table 11 (cont’d)
Summary of Exploratory Factor Analysis Results for Motivations (N = 296)
Factor title, indicator, and item EFA Loading
To show off. .80
Factor 3: Perceived Functionality (α = .86)
Because it is easy to use. .48
Because it is casual. .68
Because it is functional. .72
Because it is convenient. .76
Because it is real. .74
Factor 4: Entertainment (α = .85)
To pass the time when bored. .59
Because it is entertaining. .81
Because it is enjoyable. .82
Because it is fun. .82
Factor 5: Social Sharing (α = .83)
To share information about me (e.g., feelings, updates, etc.). .71 To share information I think is interesting (e.g., reposting). .70
To promote certain topics. .42
To see what other people share. .52
To record things that happen in my daily life. .71
To receive responses from others. .53
To feel like I belong to a community. .43
Factor 6: Interaction (α = .75)
To have conversations with others (e.g., chats, gossip, etc.). .66 To maintain a good relationship with others (for networking). .59 To meet/connect with others who have similar interests. .51 Because I can receive some benefits (e.g., giveaways,
Because it disappears after 24 hours. .78
Factor 8: Surveillance (r = .59)
To keep in touch with family and friends. .80
To get updates on my family and friends. .74
Note: means for a 7-point scale (strongly disagree = 1; disagree = 2; somewhat disagree = 3; neutral = 4; somewhat agree = 5; agree = 6; strongly agree = 7).