Do new media level the playing field during election campaigns (‘equalization’) or do they mirror existing inequalities between parties (normalization)? Empirical studies come to contradictory findings. Part of the answer is in the timing: first social media level the playing field, afterwards bigger parties see the benefit and invest in it. Yet, this raises a new question: given that social media are cheap and easy to use, how can investing in them tip the balance? Based on a critical assessment of the literature and in-depth interviews, we advance a new theoretical framework to address both contradictions: the motivation-resource-based diffusion model. We link this model to the broader party and campaigning literature and formulate expectations, in terms of party size and ideology, about which parties use social media professionally. Afterwards, we conduct a crisp-set qualitative comparative analysis (QCA) of the Dutch parties (2010 and 2012 elections) to assess these expectations. We find that populism, postmaterialism, and party size matter but in different ways in the different phases of diffusion.
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The underlying assumption in the normalization versus equalization literature is that new technologies benefit their users because professional use of these communication channels can contribute to winning votes, influencing policy debates and outcomes, and even in gaining positions of power. All of these have been labelled central rational goals of politicians (Strøm 1990).
Still, it could be that 2 years is too short to see normalization taking place. Indeed if one observes no normalization, this could be an artefact of a time frame that is too short. However, our results do show a shift from equalization to normalization between 2010 and 2012, which by itself is a testament of how fast developments went during our time frame.
This refers to the "relational dimension" of the normalization–equalization debate: other dimensions are important too, but it goes beyond the scope of this study to investigate those as well.
One could, for instance, suggest that over time social media use becomes more professionalized and thereby more expensive (cf. Vaast and Kaganer 2013). Professionalization could indeed be one factor at play with respect of the cost of using social media. However, this still does not tell us how social media use becomes more expensive, which is important to understand whether it becomes too expensive for smaller parties and which parties can circumvent the issue of higher monetary costs.
Some comparative studies also include the electoral system (Strandberg 2008), in our one-country study this factor is constant.
This analysis of which motivations and resources exist is based on interviews in a flexible list system (the Netherlands). While we generate more general building blocks from these interviews (i.e. our theoretical models is applicable to other systems), the relative impact of the different motivations and resources that we will distinguish might differ. In the Conclusion, we will reflect on what this means particularly for less flexible list systems (e.g. Spain) and for hyper-personalized systems (e.g. UK).
From the interviews: “access to advanced software … generates all kinds of new statistics and a lot more data. That is really useful when experimenting” (Interview #3).
From the interviews: “A lot of people say social media are cheap. But if you want to do it well, it does cost money. Our most successful posts last year were infographics. If you want to make it look well, it costs money” (Interview #5).
From the interviews: “[Time allows me to] “make sure that everybody gets an answer to her question within the hour” (Interview #4). This social media manager used more expensive software and monitored the politicians' time to answer questions. When it took too long, the party answered for them.
Others echoed this: “we are constantly reading the news and thinking of things and ways to post it on social media” (Interview #8).
The importance of where the voters are also featured in another interview, where the social media manager was ahead of the rest of the party: “I had to convince them and show the value of it, (…) it took a while” (Interview #9).
It should be noted that our model is a theoretical one: it is a starting point to formulate expectations for empirical analyses. These expectations can actually be about other new technologies as well: the building blocks (motivations and resources) are likely to be similar.
The tension between the populist party leader and the rest of the party has also been noticed by Dolezal (2015, p. 115) in the Austrian context. While the party leader, Strache, was actively using social media, the rest of the party lagged behind.
It also makes the Netherlands a most likely case for equalization (cf. Strandberg 2008); if we find no equalization here, it will be unlikely elsewhere.
The calibration of variables has been subject to discussion as QCA results have been shown to be sensitive to decisions made in this step (e.g. Krogslund et al. 2015; Paine 2016; Skaaning 2011). However, replication studies showed this to be most problematic for fsQCA, not csQCA (see Skaaning 2011, pp. 398–399).
We do acknowledge that not all other parties are equally small and that the three classic parties have lost some of their dominance in the recent elections. As a sensitivity tests, we also ran analyses including D66, PVV, and SP among ‘BIG’. Where relevant, this is discussed in Results section (Section “Bringing in the logical remainders (Step 5)”).
Including CU2012 does not change this conclusion.
Coding CU2012 as a positive case would mean that (4a) only holds for populist parties, not for all smaller, non-postmaterialist opposition parties.
Populist parties consider 'the people' homogeneous; postmaterialist parties heterogeneous/pluralist.
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We would like to express our gratitude to the three anonymous reviewers whose useful feedback significantly strengthened the final version of this article. In addition, we are thankful to the interviewees for their time and insights and Dr. Liesbeth Hermans for her thorough and critical feedback on an earlier version of this work. All remaining flaws are ours.
See Table 4.
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Spierings, N., Jacobs, K. Political parties and social media campaigning. Acta Polit 54, 145–173 (2019). https://doi.org/10.1057/s41269-018-0079-z
- Election campaigns
- Social media
- Political parties