Social Media,Dreaming,and Personality: An Online Study

Abstract

Social media consumption plays an important role in everyday life and, thus, one would expect that this topic is reflected in dreams. This online survey included 1,349 participants (763 women, 586 men) completing questions about social media use in waking, percentage of social media dreams, and the Big Five personality dimensions. Social media dreams were quite rare (two percent of all remembered dreams), but their frequency correlated with neuroticism and extraversion—in addition to the amount of time using social media in waking—supporting the hypothesis that social media have a stronger effect on those person's inner life due to the higher importance attached to this channel of communication. For future research it would be of interest to elicit emotions related to social media in waking and the emotional tones of social media dreams to study whether positive and/or negative aspects of waking-life social media use are directly reflected in dreams.

Introduction

Dreaming is defined as subjective experiences during sleep that can be recalled upon awakening.¹ According to the continuity hypothesis of dreaming,² dream content reflect waking life experiences. That is, if participants are engaged in activities like sports,³ driving a car,⁴ playing/listening to music,⁵ or playing video games⁶ in waking life, they dream often about it. In addition to this general relationship, it has been demonstrated that emotionally intense waking life experiences are more often incorporated into dreams than mundane experiences.^7–9 that is, dream content not only reflects the amount of time spent with a particular activity but also the personal significance and involvement of the waking life experience.¹ Looking at very salient life events like war experiences, the findings indicated that this topic can show up in dreams even decades later.¹⁰

Research also focused on possible functions of dreaming like the Threat Simulation Theory¹¹ and the Social Simulation Theory¹²; these theories emphasize that dreaming is a practice field for learning and perfecting important skills. The findings that dream content reflect sleep-dependent memory consolidation^13–16 fits within this framework, persons who have task-related dreams showed better performance on the following day. To summarize, dreams can inform us about personal significance of waking-life experiences and might reflect those experiences which are long lasting because these are consolidated during sleep.

Social media use is widespread in the general population; in 2017, more than 55 percent of the population in Germany used social media for private communications during the last 3 months, with very high rates in young adults (almost 90 percent) to lower rates in the elderly (about 20 percent).¹⁷ Despite this prominent role in waking life, research on the effects of social media on dreams is relatively scarce. Moverley et al.¹⁸ showed that the amount of time using social media in waking life correlated positively with the percentage of social media dreams.

The findings of Jayne Gackenbach's research group suggested than social media use might be associated with problematic dreaming, for example, more aggression and less friendliness in most recent dreams of social media users¹⁹ and persons starting to use social media at a very young age reported more often bad dreams.²⁰ As social media use is related to low emotional stability in large-scale surveys in different countries,²¹ studying dreams in social media users might help to understand the motivation of using social media and possible effects of social media use on the person's inner life.

The present study analyzed a subsample of a study by Moverley et al.,¹⁸ who also—within the context of another study—completed a Big Five Personality Inventory. It was hypothesized that neuroticism (low emotional stability) is related to the percentage of social media dreams as social media use in persons with high neuroticism might be related to distressing topics like loneliness, social anxiety, or exclusion, and these more emotionally intense waking-life experiences are more likely to be incorporated into dreams.^7,8

Materials and Methods

Participants

Overall, 1,966 participants (1,141 women and 825 men) completed the online survey regarding media and dreaming between April 8, 2016 and April 18, 2016.¹⁸ Of this sample, 1,349 participants (763 women, 586 men) completed the German version of the NEO-Five-Factor-Inventory (NEO-FFI-30) within another study carried out between March 23, 2015 and April 8, 2015 within the same panel. This sample had a mean age of 49.28 ± 14.26 years (range: 19–91 years). The distribution concerning education was the following: not finished school (n = 5), 9 years of school (“Hauptschule”; n = 142), O-level (“Mittlere Reife”; n = 405), A-levels (“Fach-/Hochschulreife”; n = 305), university (n = 448), and doctorate (n = 44).

Measurement instruments

The dream recall frequency was measured by a 7-point-scale (0 = never, 1 = less than once a month, 2 = about once a month, 3 = 2 to 3 times a month, 4 = once a week, 5 = several times a week, 6 = almost every morning); a scale with a high retest reliability of r = 0.756.²²

The section with items regarding social media started with a definition: “Social media are all media that enable social interactions (Examples: facebook, whatsapp, Instagram, commenting on youtube).” How many percent of your dreams included social media topics? (Please enter a distinct number. If your dreams do not include the topic, please enter 0.) How many hours per week do you spend on average with social media? (Please enter a distinct number. Please consider the time during the week and at weekends.) How involved are you while doing this? (0 = not at all, 1 = somewhat, 2 = partly, 3 = fairly, and 4 = very much). There was also the option “I am not doing that.”

To measure the Big Five personality factors, the German version of the NEO-FFI-30 by Körner et al.²³ has been used. Each factor has been computed as a average score of six corresponding items for each trait. Internal consistencies (Cronbach's α) for this version of the NEO-FFI ranged between r = 0.67 (openness to experience) and r = 0.81.²³

Procedure

An e-mail with links to the studies was sent to persons registered within the online panel www.wisopanel.net; those persons who were interested to participate in online studies, gave consent to be contacted if a new study was carried out, and had heterogenic demographic backgrounds. For some surveys, prizes or money are given for participation, but these two studies were voluntary and unpaid. Statistical procedures were carried out using SAS for Windows 9.4. As the percentage of social media dreams was not normally distributed, social media percentages were grouped into several categories. We carried out ordinal regression analyses to test the association between the percentage of social media dreams, social media use in waking and involvement in social media use, personality, and controlled for potentially confounding variables like age, gender, education and dream recall frequency. Sample sizes are slightly reduced due to missing values.

Results

Overall, the dream recall frequency was distributed as follows (n = 1,349): Almost every morning (8.67 percent), several times a week (23.28 percent), about once a week (18.68 percent), about 2–3 times a month (15.49 percent), about once a month (9.71 percent), less than once a month (16.98 percent), and never (7.19 percent). The mean and standard deviations of the five factors of the NEO-FFI were: neuroticism (8.87 ± 5.55, n = 1,348), extroversion (12.50 ± 4.02, n = 1,348), openness to experience (14.88 ± 4.41, n = 1,348), agreeableness (17.12 ± 4.02, n = 1,347), and conscientiousness (17.90 ± 3.63, n = 1,349).

For the total group, the average use of social media was 4.04 ± 6.83 hours per week (n = 1,327). Five hundred-twelve participants stated that they have not used social media. The mean involvement was 1.92 ± 0.92 (n = 811) with the following distribution: not at all (6.66 percent), somewhat (26.76 percent), partly (38.47 percent), fairly (24.29 percent), and very much (3.82 percent). This indicates that only a small group was deeply involved in social media. Involvement correlated with social media use: r = 0.383 (p < 0.001, n = 791).

The mean percentage of social media dreams was 2.15 percent ±7.27 percent, that is, a relatively small percentage of the remembered dreams included social media topics. As the distribution was skewed, the individual percentages were categorized into six groups (Table 1) to compute ordinal regressions.

Table 1.

Participants' Reported Percentage of Dreams Within Social Media Grouped into Six Categories (n = 1,329)

Percentage of media dreams	Frequency	Percentage
40.01–100	10	0.75
20.01–40.00	21	1.58
10.01–20.00	32	2.41
5.01–10.00	67	5.04
0.01–5.00	111	8.35
0	1,088	81.87

Younger age and lower education was associated with higher social media use (Table 2). In addition, neuroticism and extroversion were also related to higher social media use. For the subsample with social media use, involvement in this activity was only related to extroversion.

Table 2.

Parametric Regressions for the Social Media Variables

Variable	Social media use (hours/week) (n = 1,322)			Social media involvement (n = 808)
Variable	SE	t	p	SE	t	p
Age	−0.1390	−4.9	<0.0001	−0.0213	−0.6	0.5566
Gender (1 = female, 0 = male)	0.0189	0.7	0.5120	0.0649	1.8	0.0809
Education	−0.0817	−2.2	0.0256	−0.0311	−0.9	0.3839
Neuroticism	0.1180	3.5	0.0005	0.0776	1.8	0.0702
Extraversion	0.1097	3.6	0.0003	0.1813	4.7	<0.0001
Openness to experience	0.0448	1.0	0.1115	0.0650	1.8	0.0737
Agreeableness	−0.0344	−1.2	0.2518	−0.0014	−0.0	0.9710
Conscientiousness	0.0199	0.6	0.5210	0.0151	0.4	0.7043

Analysis includes age, gender, education, and all five personality factors entered simultaneously.

SE, standardized estimates.

In Table 3, the ordinal regressions for the categorized percentages of social media dreams are depicted. All variables like age, gender, education, dream recall frequency, social media variables, and all five personality factors were entered simultaneously. For the total group, the amount of time spent with social media in waking life was related to the percentage of social media dreams. In addition, neuroticism and extroversion were also correlated—keeping in mind that the amount of social media use in waking life, which is also related to these two traits was statistically controlled.

Table 3.

Ordinal Regression for the Categorized Percentage of Social Media Dreams

Variable	Analysis 1 (n = 1,315)			Analysis 2 (n = 782)
Variable	SE	χ²	p	SE	χ²	p
Age	−0.1679	14.0	0.0002	−0.1161	6.0	0.1444
Gender (1 = female, 0 = male)	−0.1813	15.6	<0.0001	−0.1879	15.1	<0.0001
Education	−0.0513	1.4	0.2447	−0.0634	1.9	0.1729
Dream recall frequency	0.2165	20.5	<0.0001	0.1917	15.1	0.0001
Social media use (hours/week)	0.3065	85.4	<0.0001	0.1244	8.4	0.0038
Social media involvement	—			0.2796	31.7	<0.0001
Neuroticism	0.2228	18.1	<0.0001	0.2161	14.7	0.0001
Extraversion	0.1486	9.9	0.0016	0.1039	4.1	0.0727
Openness to experience	0.0375	0.7	0.4085	−0.0145	0.1	0.7642
Agreeableness	−0.0243	0.3	0.5907	−0.0842	3.0	0.0827
Conscientiousness	−0.0169	0.1	0.7192	−0.0186	0.1	0.7091

Analysis includes age, gender, education, dream recall frequency, social media variables, and all five personality factors entered simultaneously.

SE, standardized estimates.

Similarly, younger age was associated with a lower percentage of social media dreams; men tend to report higher percentages of social media dreams than women. Education, openness to experience, agreeableness, and conscientiousness were not related to social media dream percentage. Lastly, dream recall frequency was positively related to the percentage of social media dreams. The subgroup of participants showed a similar pattern if the involvement variable was added to the regression analysis (Table 3). Interestingly, the involvement variable was more closely associated with the percentage of social media dream percentage than the amount of time spent with social media. Neuroticism and extroversion were again correlated with the social media dream percentage.

Discussion

Overall, 61.4 percent of the participants reported using social media—a figure that is representative for Germany.¹⁷ Social media dreams were quite rare (two percent of all remembered dreams), but their frequency correlated with neuroticism and extraversion—in addition to the amount of time using social media in waking—supporting the hypothesis that social media have a stronger effect on those persons' inner life due to the higher importance attached to this channel of communication. An unexpected finding which warrants further study is the higher percentages of social media dreams in males.

Several limitations concerning the methodology have to be discussed. First, the retrospective estimates of social media dream percentage might not be that accurate due to memory; however, comparing percentages of sport dreams from a similar retrospective measure with a diary study using dream content analysis indicated that these subjective and retrospective estimates are quite accurate.^3,24 The significant correlation between percentage of social media dreams and dream recall frequency in our study might implicate that low dream recallers might forget dreams that included social media topics and, thus, underestimate their “real” social media dream percentage. To avoid this retrospective bias, it would be necessary to carry out diary studies over a longer time period so low dream recallers can also contribute a substantial number of dreams.²⁵

Similarly, the amount of time spend with social media during the day might be underestimated by the participants providing retrospective estimates for the last week. As heavy users constitute only a small part of the sample, the underestimation might not be that significant, but using modern sample techniques could provide more exact data on social media use.

Although the sample showed a large age range, it is not representative regarding dream recall frequency; as participants were asked to participate in a dream study, the sample is biased toward people who are interested in the dream topic.²² In addition, social backgrounds of the sample are more likely to include academics compared with representative data,²⁶ including education in the analyses showed little effects, except the slightly higher social media use in persons with lower education. This methodological issue underlines the importance to control the regression analyses for dream recall frequency. Data were collected in 2016; as social media use and related attitudes toward social media might change within short time ranges it would be interesting to replicate this study from time to time. For measuring social media use in waking, only two items were used (amount of time and involvement). One might speculate that more sophisticated questionnaires for example,¹⁹ might be helpful in analyzing the effect of specific social media activities or emotions associated with social media use on dreaming.

Close to the figures reported for the German sample in the study by de Zúñiga et al.,²¹ we found an association between neuroticism and general social media use and extroversion and social media use supporting the validity of the present findings.

Overall, the percentage of social media dreams was relatively small (about two percent), lower than the percentage of music dreams 6.30 percent²⁷; or TV-related dreams about five percent.¹⁸ Despite the small social media dreams percentage, the amount of time using social media during waking was related to this percentage—like in the total sample reported in Moverley et al.¹⁸—supporting the continuity hypothesis of dreaming.²⁸ As expected, social media dream percentage is related to neuroticism—even if the amount of time spent with social media in waking (which is itself related to neuroticism) is statistically controlled. As persons with high neuroticism scores deal more often with depressive moods and/or anxieties, one might speculate that social media are more important to them.

As neuroticism is related to nightmare frequency,²⁹ it is very likely that the social media dreams of persons with high neuroticism scores are more negatively toned. In addition to the positive aspects of social media offering an opportunity to keep in touch, there are also negative aspects like cyberbullying.³⁰ It would be very interesting to expand the present study to look into the emotional quality of social media dreams. Music dreams, for example, are on average more positively toned than dreams without music,³¹ but music students also reported very negatively toned dreams, for example, not performing well.⁵

As mentioned above, it would also be of interest to include items about the emotions associated with social media use in waking. As social relationships are more important to extraverts compared with introverts,³² the finding of the relationship between extroversion and the social media dreams percentage also supports the hypothesis that salient waking life experiences (here: social media use) are more often incorporated into dreams than less salient ones.^7,8 Although there might be stereotypes regarding social media users, a large multinational study²¹ clearly indicate a small but substantial positive relation between extroversion and social media use—compatible with the present findings.

Similarly, one might hypothesize that interaction through social media is more important to young adults, therefore the decline of social media dream percentage with age (again controlled for actual social media use in waking) might reflect the importance of involvement on the incorporation into dreams. This is also reflected in the stronger effect of involvement compared with time spent using social media in the subgroup of social media users. Although there was no gender difference in social media use and social media involvement, men reported higher percentages of social media dreams than women—controlled for age, dream recall frequency, and the Big Five personality factors. As this finding was completely unexpected, further research is necessary to explain this phenomenon. One possible explanation might be that men use social media channels in relation to online gaming³³ and, thus, the exchange with other gamers might be salient and, thus, result in more social media dreams even though the amount of time spent with social media and the involvement did not differ between the sexes. For future research it would be very interesting to include some questions about content of social media exchanges.

To summarize, the present findings indicate that social media dream frequency not only reflect the amount of time using social media during waking but also the emotional involvement with social media as persons with high neuroticism scores and/or high extroversion scores reported more social media dreams. For future research it would be of interest to elicit emotions related to social media in waking and the emotional tones of social media dreams to study whether positive and/or negative aspects of waking-life social media use are directly reflected in dreams. If social media dreams reflect the downsides of social media use (we would expect this relationship), these distressing dreams might offer a venue for therapeutic interventions for persons with problematic social media use.³⁴

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

References

Schredl

(2018) Researching dreams: the fundamentals. Cham: Palgrave Macmillan.

Hall

, Nordby

. (1972) The individual and his dreams. New York: New American Library.

Schredl

, Erlacher

. Relationship between waking sport activities, reading and dream content in sport and psychology students. The Journal of Psychology, 2008; 142:267–275.

Schredl

, Hofmann

. Continuity between waking activities and dream activities. Consciousness and Cognition, 2003; 12:298–308.

Vogelsang

, Anold

, Schormann

, Wübbelmann

, Schredl

. The continuity between waking-life musical activities and music dreams. Dreaming, 2016; 26:132–141.

Gackenbach

, Bown

. (2019) The effects of media on dreaming. In: Valli

, Hoss

, eds. Dreams: understanding biology, psychology, and culture, Vol. 1. Santa Barbara: Greenwood, pp. 219–224.

Schredl

Factors affecting the continuity between waking and dreaming: emotional intensity and emotional tone of the waking-life event. Sleep and Hypnosis, 2006; 8:1–5.

Malinowski

, Horton

. Evidence for the preferential incorporation of emotional waking-life experiences into dreams. Dreaming, 2014; 24:18–31.

Vallat

, Chatard

, Blagrove

, et al. Characteristics of the memory sources of dreams: a new version of the content-matching paradigm to take mundane and remote memories into account. PLoS One, 2017; 12:e0185262.

10.

Schredl

, Piel

. War-related dream themes in Germany from 1956 to 2000. Political Psychology, 2006; 27:299–307.

11.

Revonsuo

, Valli

. Dreaming and consciousness: testing the threat simulation theory of the function of dreaming. Psyche: An Interdisciplinary Journal of Research on Consciousness, 2000; 6:1–24.

12.

Revonsuo

, Tuominen

, Valli

. (2015) The avatars in the machine. In: Metzinger

, Windt

, eds. Open MIND. Frankfurt am Main: MIND Group, pp. 1–28.

13.

Wamsley

, Stickgold

. Dreaming of a learning task is associated with enhanced memory consolidation: replication in an overnight sleep study. Journal of Sleep Research, 2019; 28:1–8.

14.

Wamsley

, Tucker

, Payne

, et al. Dreaming of a learning task is associated with enhanced sleep-dependent memory consolidation. Current Biology, 2010; 20:850–855.

15.

Schoch

, Cordi

, Schredl

, et al. The effect of dream report collection and dream incorporation on memory consolidation during sleep. Journal of Sleep Research, 2019; 28:e12754.

16.

Klepel

, Schredl

. Correlation of task-related dream content with memory performance of a film task—a pilot study. International Journal of Dream Research, 2019; 12:112–118.

17.

Statistisches Bundesamt. (2018) Statistisches Jahrbuch 2018—7. Kultur, Medien, Freizeit. https://www.destatisde/DE/Themen/Querschnitt/Jahrbuch/jb-kultur-medien-freizeitpdf?__blob=publicationFile&v=6 (accessed Jun. 10, 2019).

18.

Moverley

, Schredl

, Göritz

. Media dreaming and media consumption—an online study. International Journal of Dream Research, 2018; 11:127–134.

19.

Gackenbach

, Boyes

. Social media versus gaming associations with typical and recent dreams. Dreaming, 2014; 24:182–202.

20.

Gackenbach

, Gahr

. Media use and dream associations between Canadians of differing cultural backgrounds. International Journal of Dream Research, 2015; 8:2–9.

21.

de Zúñiga

, Diehl

, Huber

, et al. Personality traits and social media use in 20 countries: how personality relates to frequency of social media use, social media news use, and social media use for social interaction. CyberPsychology, Behavior and Social Networking, 2017; 20:540–552.

22.

Schredl

, Berres

, Klingauf

, et al. The Mannheim Dream questionnaire (MADRE): retest reliability, age and gender effects. International Journal of Dream Research, 2014; 7:141–147.

23.

Körner

, Geyer

, Roth

, et al. Personlichkeitsdiagnostik mit dem NEO-Fünf-Faktoren-Inventar: Die 30-Item-Kurzversion (NEO-FFI-30) [Personality diagnostic using the NEO-Five-Factor-Inventory: the 30-Item short version (NEO-FFI-30)]. Psychotherapie, Psychosomatik und Medizinische Psychologie, 2008; 58:238–245.

24.

Erlacher

, Schredl

. Dreams reflecting waking sport activities: a comparison of sport and psychology students. International Journal of Sport Psychology, 2004; 35:301–308.

25.

Schredl

Questionnaire and diaries as research instruments in dream research: methodological issues. Dreaming, 2002; 12:17–26.

26.

Statistisches Bundesamt. (2018) Bevölkerung nach Bildungsabschluss in Deutschland. https://www.destatisde/DE/ZahlenFakten/GesellschaftStaat/BildungForschungKultur/Bildungsstand/Tabellen/Bildungsabschlusshtml (accessed May 14, 2018).

27.

König

, Fischer

, Friedemann

, et al. Music in dreams and music in waking: an online study. Psychomusicology: Music, Mind, and Brain, 2018; 28:65–70.

28.

Schredl

Continuity between waking and dreaming: a proposal for a mathematical model. Sleep and Hypnosis, 2003; 5:38–52.

29.

Levin

, Nielsen

. Disturbed dreaming, posttraumatic stress disorder, and affect distress: a review and neurocognitive model. Psychological Bulletin, 2007; 133:482–528.

30.

Whittaker

, Kowalski

. Cyberbullying via social media. Journal of School Violence, 2015; 14:11–29.

31.

König

, Schredl

Music in dreams: a diary study. Psychology of Music, 2019 (in press); DOI: 10.1177/0305735619854533.

32.

Shiraev

(2017) Personality theories: a global view. Los Angeles: SAGE.

33.

Trepte

, Reinecke

, Juechems

. The social side of gaming: how playing online computer games creates online and offline social support. Computers in Human Behavior, 2012; 28:832–839.

34.

Pesant

, Zadra

. Working with dreams in therapy: what do we know and what should we do?. Clinical Psychology Review, 2004; 24:489–512.