Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter Mouton March 8, 2023

Influencers as political agents? The potential of an unlikely source to motivate political action

  • Brigitte Naderer EMAIL logo
From the journal Communications

Abstract

The impact of social media influencers (SMIs) on brand-related outcomes has been well researched, yet whether this influence also impacts political participation and what role the relationship between SMIs and their audiences play has not been sufficiently examined to date. Basing this study on the Balance Model, I investigated the potential of an unlikely vs. a likely source and the role of similarity with a SMI based on a shared topic interest to elicit the intention for political action in an experimental study (n = 222). The perceived similarity with the SMI was examined as a mediator and the role of the shared topic interest with the SMI as a potential moderator. The results indicate that a likely source for political information generated a greater topic fit. The perceived similarity with the source depended on the shared topic interest between the source and the participants. This is a key finding, as perceived similarity with the source in turn predicted the intention to take political action, which positively activated participants who shared the topic interest of the unlikely source even if they did not indicate a topic interest in politics. Thus, a shared interest with a SMI might make even those not interested in politics more open to political participation.


Article Note

I offer an OSF link of the data, so additional comparisons and analyses can be conducted: https://osf.io/6wgx4/?view_only=f41a0064cb7d43c0bbc188aa59498143.


References

Abidin, C. (2016). “Aren’t these just young, rich women doing vain things online?”: Influencer selfies as subversive frivolity. Social Media+ Society, 2, 1–17.10.1177/2056305116641342Search in Google Scholar

Ballantine, P. W., & Yeung, C. A. (2015). The effects of review valence in organic versus sponsored blog sites on perceived credibility, brand attitude, and behavioural intentions. Marketing Intelligence & Planning, 33, 508–521.10.1108/MIP-03-2014-0044Search in Google Scholar

Berscheid, E. (1966). Opinion change and communicator-communicatee similarity and dissimilarity. Journal of Personality and Social Psychology, 4, 670.10.1037/h0021193Search in Google Scholar

Boulianne, S. (2015). Social media use and participation: A meta-analysis of current research. Information, Communication & Society, 18, 524–538.10.1080/1369118X.2015.1008542Search in Google Scholar

Boulianne, S. (2019). Revolution in the making? Social media effects across the globe. Information, Communication & Society, 22, 39–5410.1080/1369118X.2017.1353641Search in Google Scholar

Breves, P. L., Liebers, N., Abt, M., & Kunze, A. (2019). The perceived fit between Instagram influencers and the endorsed brand: How influencer–brand fit affects source credibility and persuasive effectiveness. Journal of Advertising Research, 59, 440–454.10.2501/JAR-2019-030Search in Google Scholar

Burnstein, E., Stotland, E., & Zander, A. (1961). Similarity to a model and self-evaluation. The Journal of Abnormal and Social Psychology, 62, 257.10.1037/h0043981Search in Google Scholar

Casaló, L. V., Flavián, C., & Ibáñez-Sánchez, S. (2020). Influencers on Instagram: Antecedents and consequences of opinion leadership. Journal of Business Research, 117, 510–519.10.1016/j.jbusres.2018.07.005Search in Google Scholar

Chang, C. (2011). Opinions from others like you: The role of perceived source similarity. Media Psychology, 14, 415–441.10.1080/15213269.2011.620539Search in Google Scholar

Cohen, J., Weimann-Saks, D., & Mazor-Tregerman, M. (2018). Does character similarity increase identification and persuasion? Media Psychology, 21, 506–528.10.1080/15213269.2017.1302344Search in Google Scholar

Colliander, J., & Dahlén, M. (2011). Following the fashionable friend: The power of social media: Weighing publicity effectiveness of blogs versus online magazines. Journal of Advertising Research, 51, 313–320.10.2501/JAR-51-1-313-320Search in Google Scholar

Dambeck, H. (2019). Der Rezo-Effekt – echt oder nur gefühlt? [The Rezo effect – real or only perceived?] Spiegel Online. Retrieved December 10, 2020 from https://www.spiegel.de/politik/deutschland/rezo-effekt-hat-er-der-cdu-geschadet-oder-den-gruenen-genuetzt-a-1270620.html.Search in Google Scholar

De Jans, S., Spielvogel, I., Naderer, B., & Hudders, L. (2021). Digital food marketing to children: How an influencer’s lifestyle can stimulate healthy food choices among children. Appetite, 162, 105–182.10.1016/j.appet.2021.105182Search in Google Scholar

De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: The impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36(5), 798–828.10.1080/02650487.2017.1348035Search in Google Scholar

Ekström, M., Olsson, T., & Shehata, A. (2014). Spaces for public orientation? Longitudinal effects of internet use in adolescence. Information, Communication & Society, 17, 168–183.10.1080/1369118X.2013.862288Search in Google Scholar

Enke, N., & Borchers, N. S. (2019). Social media influencers in strategic communication: A conceptual framework for strategic social media influencer communication. International Journal of Strategic Communication, 13(4), 261–277.10.1080/1553118X.2019.1620234Search in Google Scholar

Feick, L., & Higie, R. A. (1992). The effects of preference heterogeneity and source characteristics on ad processing and judgements about endorsers. Journal of Advertising, 21, 9–24.10.1080/00913367.1992.10673364Search in Google Scholar

Gaenssle, S., & Budzinski, O. (2021). Stars in social media: New light through old windows? Journal of Media Business Studies, 18, 79–105.10.1080/16522354.2020.1738694Search in Google Scholar

Gil de Zúñiga, H., Molyneux, L., & Zheng, P. (2014). Social media, political expression, and political participation: Panel analysis of lagged and concurrent relationships. Journal of Communication, 64, 612–634.10.1111/jcom.12103Search in Google Scholar

Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford PressSearch in Google Scholar

Heiss, R., & Matthes, J. (2019). Does incidental exposure on social media equalize or reinforce participatory gaps? Evidence from a panel study. New Media & Society, 21, 2463–2482.10.1177/1461444819850755Search in Google Scholar

Hudders, L., De Jans, S., & De Veirman, M. (2020). The commercialization of social media stars: A literature review and conceptual framework on the strategic use of social media influencers. International Journal of Advertising, online-first, 1–49.10.4324/9781003181286-3Search in Google Scholar

Hwang, K., & Zhang, Q. (2018). Influence of parasocial relationship between digital celebrities and their followers on followers’ purchase and electronic word-of-mouth intentions, and persuasion knowledge. Computers in Human Behavior, 87, 155–173.10.1016/j.chb.2018.05.029Search in Google Scholar

Kamins, M. A., & Gupta, K. (1994). Congruence between spokesperson and product type: A matchup hypothesis perspective. Psychology & Marketing, 11, 569–586.10.1002/mar.4220110605Search in Google Scholar

Kapitan, S., & Silvera, D. H. (2016). From digital media influencers to celebrity endorsers: Attributions drive endorser effectiveness. Marketing Letters, 27, 553–567.10.1007/s11002-015-9363-0Search in Google Scholar

Karnowski, V., Kümpel, A. S., Leonhard, L., & Leiner, D. J. (2017). From incidental news exposure to news engagement. How perceptions of the news post and news usage patterns influence engagement with news articles encountered on Facebook. Computers in Human Behavior, 76, 42–50.10.1016/j.chb.2017.06.041Search in Google Scholar

Katz, E. (2015). Where are opinion leaders leading us? International Journal of Communication, 9, 1023–1028.Search in Google Scholar

Katz, E., & Lazarsfeld, P. F. (1955). Personal influence: The part played by people in the flow of mass communications. Abingdon, UK: Routledge.Search in Google Scholar

Kim, Y., Chen, H. T., & Gil de Zúñiga, H. (2013). Stumbling upon news on the internet: Effects of incidental news exposure and relative entertainment use on political engagement. Computers in Human Behavior, 29, 2607–2614.10.1016/j.chb.2013.06.005Search in Google Scholar

Knoll, J., Matthes, J., & Heiss, R. (2020). The social media political participation model: A goal systems theory perspective. Convergence, 26, 135–156.10.1177/1354856517750366Search in Google Scholar

Kümpel, A. S. (2019). The issue takes it all? Incidental news exposure and news engagement on Facebook. Digital Journalism, 7, 165–186.10.1080/21670811.2018.1465831Search in Google Scholar

Liljander, V., Gummerus, J., & Söderlund, M. (2015). Young consumers’ responses to suspected covert and overt blog marketing. Internet Research, 25, 610–632.10.1108/IntR-02-2014-0041Search in Google Scholar

Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19, 58–73.10.1080/15252019.2018.1533501Search in Google Scholar

Mishra, A. S., Roy, S., & Bailey, A. A. (2015). Exploring brand personality–celebrity endorser personality congruence in celebrity endorsements in the Indian context. Psychology & Marketing, 32, 1158–1174.10.1002/mar.20846Search in Google Scholar

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58, 20–38.10.1177/002224299405800302Search in Google Scholar

Naderer, B., Heiss, R., & Matthes, J. (2020). The skilled and the interested: How personal curation skills increase or decrease exposure to political information on social media. Journal of Information Technology & Politics, online-first, 1–9.10.1080/19331681.2020.1742843Search in Google Scholar

Naderer, B., Matthes, J., Schäfer, S. (2021). Effects of disclosing ads on Instagram: The moderating impact of similarity to the influencer. International Journal of Advertising, online-first.10.1080/02650487.2021.1930939Search in Google Scholar

Peter, C., & Zerback, T. (2017). The role of similarity in exemplification effect. SCM Studies in Communication and Media, 6, 71–80.10.5771/2192-4007-2017-1-71Search in Google Scholar

Prior, M. (2005). News vs. entertainment: How increasing media choice widens gaps in political knowledge and turnout. American Journal of Political Science, 49, 577–592.10.1111/j.1540-5907.2005.00143.xSearch in Google Scholar

Reinikainen, H., Munnukka, J., Maity, D., & Luoma-aho, V. (2020). ‘You really are a great big sister’–parasocial relationships, credibility, and the moderating role of audience comments in influencer marketing. Journal of Marketing Management, online-first, 1–20.10.1080/0267257X.2019.1708781Search in Google Scholar

Rifon, N. J., Choi, S. M., Trimble, C. S., & Li, H. (2004). Congruence effects in sponsorship: The mediating role of sponsor credibility and consumer attributions of sponsor motive. Journal of Advertising, 33, 30–42.10.1080/00913367.2004.10639151Search in Google Scholar

Russell, C. A., & Stern, B. B. (2006). Consumers, characters, and products: A balance model of sitcom product placement effects. Journal of Advertising, 35, 7–21.10.2753/JOA0091-3367350101Search in Google Scholar

Schmitt, J. B. (2016). Media self-efficacy and internal political efficacy as processes underlying young adults’ political participation. SCM Studies in Communication and Media, 5, 197–222.10.5771/2192-4007-2016-2-197Search in Google Scholar

Schuhwerk, M. E., & Lefkoff-Hagius, R. (1995). Green or non-green? Does type of appeal matter when advertising a green product? Journal of Advertising, 24, 45–54.10.1080/00913367.1995.10673475Search in Google Scholar

Simons, H. W., Berkowitz, N. N., & Moyer, R. J. (1970). Similarity, credibility, and attitude change: A review and a theory. Psychological Bulletin, 73, 1–16.10.1037/h0028429Search in Google Scholar

Statistik Austria (2018). Bildungsstand der Bevölkerung im Alter von 25 bis 64 Jahren, 1971 bis 2018. Retrieved September 22, 2020 from https://www.statistik.at/web_de/statistiken/menschen_und_gesellschaft/bildung/bildungsstand_der_bevoelkerung/020912.html.Search in Google Scholar

Till, B. D., & Busler, M. (2000). The match-up hypothesis: Physical attractiveness, expertise, and the role of fit on brand attitude, purchase intent and brand beliefs. Journal of Advertising, 29, 1–13.10.1080/00913367.2000.10673613Search in Google Scholar

Table 1:

Topic fit

Perceived similarity

Intention to take political action

Mean

SD

Mean

SD

Mean

SD

Likely source

5.44

1.44

3.66

1.41

3.97

1.82

Unlikely source

4.71

1.77

3.38

1.56

3.71

1.75

F(1, 219) = 11.65

p = .001

η² = .05

F(1, 219) = 1.92

p = .168

η² = .01

F(1, 219) = 1.09

p = .298

η² = .01

Note. N = 221; F(3, 217) = 4.13, p = 0.007; Pillai’s V = .05, η² = .05.

Table 2:

Variables

Perceived similarity

Intention to take political action

b

SE

b

SE

Unlikely source vs. Likely source

–0.07

0.18

0.23

0.20

Topic importance cooking

0.13+

0.07

0.06

0.08

Topic importance politics

0.21*

0.09

0.39***

0.10

Gender female

–0.01

0.19

0.30

0.21

Instagram use frequency

0.08*

0.03

0.07*

0.04

Topic fit

0.22***

0.06

0.38***

0.07

Unlikely source * Topic interest cooking

0.24*

0.10

–0.04

0.11

Unlikely source * Topic interest politics

–0.30*

0.13

–0.02

0.14

Perceived similarity

0.24**

0.07

Explained variance

.23

.39

Note. Macro PROCESS 3, Model 10 with 1,000 bootstrap sample; N = 221; Likely source condition (i. e., environmentalist) inserted as a reference group.

*** p < .001; ** p < .01; * p < .05

Table 3:

Unlikely Source vs. Likely Source → Perceived Similarity →Intention to take political action

Topic interest politics

Topic interest cooking

b

SE

LLCI

ULCI

–1 SD

–1 SD

–0.03

0.09

–0.20

0.15

–1 SD

M

0.12

0.07

–0.01

0.28

–1 SD

+1 SD

0.21

0.10

0.04

0.44

M

–1 SD

–0.15

0.08

–0.31

–0.02

M

M

0.01

0.05

–0.10

0.10

M

+1 SD

0.09

0.08

–0.03

0.27

+1 SD

–1 SD

–0.25

0.11

–0.46

–0.05

+1 SD

M

–0.11

0.08

–0.27

0.04

+1 SD

+1 SD

–0.01

0.09

–0.20

0.19

Figure 1: Visualization of the Balance Model based on Russell and Stern, 2006, p. 8.
Figure 1:

Visualization of the Balance Model based on Russell and Stern, 2006, p. 8.

Figure 2: Conceptual Model.
Figure 2:

Conceptual Model.

Figure 3: Account overview for each source condition.
Figure 3:

Account overview for each source condition.

Figure 4: Example post for each source condition.
Figure 4:

Example post for each source condition.

Figure 5: Target post for each source condition.
Figure 5:

Target post for each source condition.

Published Online: 2023-03-08
Published in Print: 2023-03-06

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 1.5.2024 from https://www.degruyter.com/document/doi/10.1515/commun-2021-0006/html
Scroll to top button