While early ideas surrounding the influence of the Internet on political participation and communication were often overtly optimistic, comparably recent years have seen the rise of online hate speech and similar issues gaining influence in a variety of online spheres. The study presented here seeks to detail the impact of positive (‘thumbs-up’) and negative (‘thumbs-down’) feedback on the popularity of politically themed YouTube videos, uploaded during the 2017 Norwegian parliamentary election. Given the apparent dearth of studies on YouTube in this regard, the insights provided here furthers our understanding regarding the drivers of online popularity during election campaigns. Specifically, results indicate that while commenting on uploaded videos appear as related to the ‘thumbs-up’ variety, video view count appear as more clearly related to the dismissive ‘thumbs-down’ feedback option. Discussing these results, the final section of the paper also provides a few suggestions for future research efforts in this vein.
Discussion and conclusions
While it is probably wise to be wary when confronted with claims about the video-sharing service YouTube as being the “most important (although by no means representative) exemplar of the user-driven, Internet-based public sphere” , the platform has nevertheless accumulated a considerable user base since its inception in 2005. Indeed, while testaments to its popularity varies based on what type of measurement criteria is employed, YouTube has been pointed to as one of the most used Web platforms in the world . As such, it is worthy of increased scholarly attention in comparison to other online services. The current paper, then, seeks to provides such insights by studying uses of YouTube in Norway, during a period of heightened interest in public issues — the 2017 parliamentary election.
Although YouTube’s initial slogan of ‘Broadcast Yourself’ set the field for a service primarily geared towards user-generated content, various professional interests have seen the potential of the specified service and have acted accordingly — such early organizational adopters include commercial entities (e.g., Castells, 2007) as well as non-commercial varieties, like public service broadcasters (e.g., Iosifidis, 2011; Moe, 2009). With the aforementioned example of elections in mind, the service under discussion has also been adopted by a series of political parties and politicians in a multitude of contexts, leading journalists, professionals and pundits to declare “YouTube Elections” during such parliamentary events in the U.S. (Lizza, 2006; Nielsen, 2010), Australia (Gibson and McAllister, 2011) as well as elsewhere. In a general sense, the adoption of YouTube as well as other, similar services by citizens, commercial entities, political hopefuls and others speak to an overall tendency regarding the growing importance of visual and video content for online communication  and it is understandable that a service supposedly providing “hitherto unseen possibilities for distributing and redistributing information”  to political parties, politicians as well as citizens would gain traction — especially given the hyped attention that usually comes coupled with technological novelties during events such as the one studied here (e.g., Larsson, 2013).
Besides its potential for politicians on the campaign trail, we need to keep the aforementioned slogan of the studied service at hand in mind. Indeed, much like for many other social media or social networking services, YouTube has been described as carrying with it the potential to “democratize political expression by creating a new grassroots outlet for the affective in politics” . The efforts presented here contributes to the political communication literature by detailing the popularity of YouTube videos uploaded during the 2017 Norwegian parliamentary election campaign. Specifically, we focus on assessing the affective publics (Papacharissi, 2014) of what could perhaps be referred to as the Norwegian YouTube sphere in that we are interested in whether politically themed videos that receive comparably large amounts of negative (visible as ‘thumbs-down’ icons on the site) or positive (‘thumbs-up’) feedback are more or less successful in terms of gaining traction — understood here as the number of views and comments. As such, the paper also aims to increase our understanding of what drives online virality — sometimes defined as “network-enhanced word of mouth” (Nahon, et al., 2011).
The Norwegian case is suitable to study in this regard for at least four reasons. First, the popularity of the platform under scrutiny in the Norwegian context is on par if not even larger when compared to the international indicators discussed briefly earlier. As of this writing in the fall of 2017, approximately 90 percent of the Norwegian population are YouTube users. In comparison with similar statistics regarding Facebook (83 percent of Norwegians are users), Twitter (26 percent) and Instagram (47 percent), YouTube thus enjoys considerable popularity in our case country (use statistics provided by Ipsos/MMI, 2017). Second, as previous comparative research concluded that “Facebook and YouTube stood out immediately as the most relevant sites to study” , the current paper will provide insights into what appears as a curious scarcity of studies into the uses of YouTube in general and in relation to political events in particular. Third, the paper makes a contribution by focusing on other social media than the oft-studied Twitter platform (e.g., Jungherr, 2014; Jungherr, 2015), and by situating such efforts in a non-U.S. context (e.g., Jungherr, 2016; Xenos, et al., 2015). Finally, we can point to the fact that while televised political advertising is banned in Norway, parties frequently use their online channels — such as YouTube — to provide audio-visual materials to those interested (Kalsnes, 2016). Enli and Skogerbø (2013) suggest that the discussed ban would make the service under scrutiny “less of an option in the Norwegian setting” . Nevertheless, Karpf  draws on U.S. examples and points to the tendency for political actors to develop video materials without intention of buying television airtime. Instead, these actors are supposedly aiming for online views, commentary, popularity — hopefully leading to newsworthiness and spread also outside their online channel of choice. With this apparent paradox in mind, the Norwegian case does indeed appear as a suitable testing ground for how different types of politicized content fare in the online setting under scrutiny here.
The paper proceeds as follows. The next section provides an overview of literature on social media and elections, focusing specifically on YouTube and on the influences identified by previous researchers regarding online popularity. Subsequently, the methods section details the steps undertaken to collect and analyse data, while the succeeding results chapter presents the findings produced. The concluding section of the paper discusses some of the key findings, examines the limitations of the work performed and provides a few suggestions for future studies related to the topic at hand.
While social media services like the one under scrutiny here are still generally considered as novel, scholarly efforts have focused on various uses of these types of platforms for over a decade. With specific regard to the field of political communication, researchers have thus begun to summarize the work performed, reflecting on future possibilities and ways forward for the scholarly community (e.g., Enli, 2017, 2015; Jungherr, 2015; Karlsen and Enjolras, 2016; Xenos, et al., 2015). While each of these authors offer slightly differing foci for their suggestions, a few commonalities can nevertheless be identified. For instance, most of them suggest that studies tend to focus on the uses of online platforms as undertaken by either politicians and the parties that they belong to, or by the citizenry from which they seek electoral support. Our current efforts seek to overcome this apparent duality by detailing the activities undertaken by all YouTube users, scrutinizing the popularity of videos uploaded during the specified election campaign and ‘tagged’ by their original uploaders so as to indicate content related to one of the major Norwegian political parties. As such, our goal here is not specifically to assess the activates undertaken by the parties themselves, but rather to provide an overarching grasp of how the sentiment functionalities — the ‘like’ and ‘dislike’ buttons — influenced the levels of views and comments reached by each politically themed video uploaded during the campaign.
The advantages of YouTube for politicians and parties are clearly recognizable when compared to the general rhetoric that is often found in conjunction with discussions regarding the uses of online technologies by users like these. For instance, use of the Internet in general and social media in particular has often described as potentially levelling the proverbial playing field between larger and smaller political actors (e.g., Gibson and McAllister, 2015; Larsson and Svensson, 2014; Rauchfleisch and Metag, 2015), and as facilitating debate and discussion between citizens and politicians up for election (e.g., Coleman and Shane, 2012; Larsson and Ihlen, 2015; Olsson, 2016). Indeed, with the platform studied here in mind, authors have suggested possibilities in line with the discussion above, as the service “potentially offers a free space for political discourse, offering new opportunities for self-expression and interaction” . With uses at the hands of politicians (e.g., Chadwick, 2009; Gibson, and McAllister, 2011) and citizens (e.g., Bryer, 2011; McKinney and Rill, 2009) alike reported primarily from the U.S. context, previous work has indeed demonstrated some of the more positive potentials of YouTube as well as other similar services in various political settings. However, uses of services like these might also come coupled with more negative repercussions.
Specifically, we must bear in mind that not all political content posted online is characterized by heartfelt support for a specific cause, party or politician. Indeed, Johnson and Perlmutter (2010) point out that “The individual viewer in a campaign crowd with a cell phone can record a candidate’s gaffe, post it on YouTube or Flickr, and within days millions will be gasping or guffawing” . One such event, often brought up in the literature as an example of negative attention, is the infamous ‘Macaca Moment’ in which U.S. senator George Allen made a series of insensitive and racist comments to one of his competitor’s co-workers (e.g., Karpf, 2012; Holbert and Geidner, 2009). The event, caught on film by an audience member during a campaign rally during the 2006 election to the U.S. Senate, was indeed uploaded to YouTube and is popularly thought of as a turning point in that particular campaign. Similarly characterized events can be pointed to at comparably later dates. For instance, 2012 U.S. presidential candidate Mitt Romney’s ‘47 percent’ remark regarding specific voter groups that could be expected to side with his opponent has in hindsight been described as detrimental to the Romney campaign (e.g., Corn, 2012). As such, the possibilities for politicians campaigning online must also be coupled with the risks of having less than favourable content reaching high levels of popularity.
As the discussion above revolved around the potential negative ramifications of less than favourable user-generated content, it is tempting to draw a parallel to the presence of such content in the campaign materials offered up by political actors. Commonly referred to as negative campaigning, such an election strategy will often involve various forms of criticisms of opponents (e.g., Larsson, 2016; Schweitzer, 2011). As such negative aspects have been shown to be more salient and more easily remembered by recipients (e.g., Lau, 1982) we expect ‘dislikes’ to yield a stronger influence over popularity than ‘likes’. Such an expectation is further strengthened by a previous study from the 2013 Norwegian parliamentary election, where the popularity of posts made by party leaders on their respective Facebook Pages was examined (Larsson, 2015c). Results indicated that posts that were primarily critical in nature succeeded in reaching higher levels of popularity in terms of likes, shares and comments. Similarly, and more in line with the methodological approach employed here, previous work has been performed detailing the influence of Facebook Reactions on the sharing of news from a selection Norwegian media industry Facebook Pages (Larsson, 2017b). Overall, the study found that positively themed Reactions (for instance, those labelled by Facebook as “Love” or “Haha”) emerged as having impeding outcomes on the willingness of Facebook Page visitors to engage by means of sharing and commenting. By contrast, more negative varieties of Facebook Reactions — most notably “Sad” and “Angry” — were found to yield adverse influences, resulting in increased sharing and commenting.
While YouTube is perhaps most commonly understood as a hosting system for streaming video, the platform under scrutiny nevertheless boasts “a distinctly social aspect [...] that reflects its social networking characteristics” . Beyond uploading and annotating their own videos, users can comment on and provide various other forms of feedback in relation to the content provided by others. While such “social affordances” (e.g., Bucher and Helmond, 2018) are indeed available to the users of many online services, such opportunities have often been framed in primarily positive or supportive ways. For instance, we can think of the possibility to ‘favorite’, ‘star’ or subsequently ‘heart/love’ messages sent on Twitter, or the functionality to similarly ‘heart/love’ Instagram posts. In comparison, and of particular relevance to our specific interest in negativity as a driver of online popularity, YouTube allows users to ‘upvote’ or ‘downvote’ uploaded videos, employing icons depicting ‘thumbs-up’ and ‘thumbs-down’ gestures. As such, while the previously mentioned Facebook Reactions functionality was only ushered in comparatively recently ((Larsson, 2017b; Stinson, 2016), YouTube has allowed their users to express what could be considered as negatively themed ‘push-button’ –feedback for a comparably extended period of time. While the precise, situated meaning of these functionalities will undoubtedly vary from user to user (e.g., Driscoll and Walker, 2014; Lomborg and Bechmann, 2014), the overarching approach employed here will nevertheless be able to provide us with insights regarding the relationship between online success (operationalized here as the number of views and comments that a certain video had reached at the time of data collection) and the number of upvotes — ‘likes’ and downvotes — ‘dislikes’ respectively.
Summing up, it would appear that previous scholarship emanating from off-line as well as online spheres largely suggests negativity to be a clear driver of interest and attention. For the present study, these results lead us to expect the negative variety of ‘push-button’ feedback available on YouTube — ‘thumbs-down’ — to be more influential with regards to popularity (views and comments) than the more positively themed ‘thumbs-up’ variety. These expectations will be tested using statistical analyses as described in the following section.
Using the tuber package for the R programming language to access the YouTube API (Sood, 2017), metadata for all YouTube videos that were tagged with the names of the leading Norwegian political parties and uploaded during the month-long stretch before the 2017 elections (which took place on 11 September) were archived and analysed. The selected approach to data collection allows us to not only assess the activities undertaken by the parties themselves — but to also compare activity resulting from their activities with the levels of feedback found in relation to the politically themed videos uploaded by others. Archiving took place on 13 September, two days after election day, which allowed for capturing some of the electoral aftermath. As such, while the results presented here does indeed provide useful insights into the ways that YouTube was employed during the specified election, we must remember that “online texts are malleable, and oftentimes constantly changing” . With this in mind, what is presented here is essentially a snapshot of the situation on YouTube right after the 2017 elections. Table 1 provides an overview of the characteristics pertaining to the main parties searched for and included in the study.
Table 1: Basic characteristics of Norwegian parties and their YouTube presences.
Note: *On day after election, 12 September 2017.
Party name (in English) Abbreviation Ideology Vote percentage 2013 Vote percentage 2017 YouTube channel subscribers* N of tagged videos
(N; % of tagged videos uploaded by party account)*
Labour Party Ap Left 30.8 27.4 2976 322
Progress Party Frp Right 16.3 15.2 1332 185
Conservative Party H Right 26.8 25 811 461
Christian Democrats Krf Right 5.6 4.2 218 80
Green Party MDG Centre 2.8 3.2 697 188
Red Party R Left 1.1 2.4 575 185
Centre Party Sp Centre/Left 5.5 10.3 225 165
Socialist Left Party Sv Left 4.1 6 448 138
Liberal Party V Centre/Right 5.2 4.4 515 170
As the Norwegian names of two of the included parties have meanings that go beyond their political connotation (Red Party — Rødt in Norwegian, Red in English; Liberal Party — Venstre in Norwegian, Left in English), the corresponding files were checked manually in order to remove data pertaining to videos that referred to these terms but that were not party- or election-related. The measures presented in the rightmost column of Table 1, then, contains the final overview of the number of videos uploaded mentioning each party in the headline or description — as well as the number and percentage of those videos that were uploaded by the party accounts themselves.
Comparing the data regarding party activity and party size (gauged here by means of vote percentages from the studied and previous elections, and by the number of YouTube channel subscribers on the day after election — 12 September), an interesting discrepancy regarding party size and activity can be noticed. Perhaps unsurprisingly, the data on vote percentages and channel subscribers appear to be mostly interrelated — comparably larger parties enjoy comparably larger numbers of subscribers. However, this same pattern does not materialise as clearly when looking at the activity undertaken in relation to the parties themselves, or indeed by the parties themselves. For the first type of activity, Table 1 shows that while the two ‘catch-all’ parties — the Labour Party and the Conservative Party — do indeed gain the most attention in this way, a series of rather small parties appear as more successful in engaging YouTube uploaders (for instance, the Green Party with an N of related videos of 188 or the Red Party with N = 185) than the third largest actor in Norwegian politics — the Progress Party (N = 185). With regard to the percentages of videos uploaded by the parties themselves, the Green Party (who uploaded close to 13 percent of related videos) could be considered as the most active — at least in relative terms.
These discrepancies pertaining to party size and activity clearly relate to the ongoing discussion of whether online services like the one under scrutiny serve to equalize or normalize the attention gained and activity undertaken by comparably smaller or larger parties (Larsson and Svensson, 2014; Margolis and Resnick, 2000; Nitschke, et al., 2016). While tendencies of equalization, suggesting that smaller parties would have a lot to gain by means of utilization of online technology, have largely been disproven, it is nevertheless interesting that the rather small Green Party emerges as comparably more active in uploading videos. This initial result also speaks to previously uncovered fervency of online activities undertaken by green or indeed environmental parties in other contexts (Gibson, 2004; Larsson, 2015b; Strandberg, 2009; Vergeer, et al., 2011).
While the overview provided above details the overarching setting in which the present study is placed, it says very little about the drivers of online popularity as defined here. Much like for previous research looking into the political uses YouTube (e.g., Kalnes, 2009; Lilleker, 2015), we will use the number of views yielded by each video as a gauge of popularity. In an attempt to diversify the research undertaken, focus will also be placed on looking at the relationship between the ’like‘ and ’dislike‘ buttons on the one hand and the number of comments made in relation to each video posted during the studied period on the other. Indeed, previous research into citizen uses of online media in political settings largely suggests that engaging in supposedly more demanding forms of interaction — such as writing comments — is less common than what is sometimes considered as less demanding modes of interacting — such as viewing videos (Larsson, 2015a, 2013; Mossberger, et al., 2013). As such, by going beyond the number of views as a measurement of popularity, the study at hand provides further insights into what drives different types of online popularity.
In order to gauge the influence of likes and dislikes on comments posted to and views yielded by the YouTube videos posted as described previously, a series of multiple regression analyses were performed. Specifically, Likes and Dislikes were employed as independent variables, while the number of comments and views for each video posted were entered as dependent variables. Granted, while the data used and the current design can make limited claims about causality — it is perfectly possible, for instance, for a user to post a comment to a video without also utilizing the Like or Dislike functionality — the analyses presented here will nevertheless be able to detail correlations between the observed phenomena. By reporting the standardized beta values emanating from these analyses, we will be able to readily compare the apparent relationship of more positive and negative themed “interactive bells and whistles”  with the popularity of videos as described above.
Starting our assessment with the number of comments, Table 2 provides further insights into the apparent drivers behind this mode of interaction.
Table 2: Multiple regression analyses analysing the influences of Likes and Dislikes on Comments made on YouTube videos.
Notes: Results presented for each individual party. Standardized beta values presented, *p < 0.05; **p < 0.01; ***p < 0.001.
Ap Frp H Krf MDG R Sp Sv V Likes .62*** 2.20*** .39*** .86*** .51*** .60*** .80*** .62*** .50*** Dislikes .29** -1.49*** .35*** -.05 .18** .29*** .03 .29*** .41*** R2
As almost all coefficients reported in Table 2 for both Likes and Dislikes emerge as positive and significant, an initial conclusion could be to dismiss the tendency for either type of feedback to have a clear influence on the dependent variable. Nevertheless, comparing the sizes of the coefficients emanating for Likes and Dislikes respectively, a couple of interesting discrepancies can be noted. First, all coefficients related to the Like functionality emerged as larger than those related to the Dislike variety. This suggests that commenting on YouTube is associated with the provision of positive rather than negative sentiments — at least the type of one-stop clicking type feedback discussed here. This tendency appears to be particularly strong for the populist right-wing Progress Party (Frp), where videos tagged with their party name emerges as most successful in terms of yielding the largest positive coefficient in Table 2. Second, the uncovered association is strengthened when one considers the largest coefficient reported for Dislikes. Again related to the Progress Party, the only negative significant beta value shown in Table Two suggests that the larger the number of Dislikes, the smaller the number of comments. Looking closer at the data, the videos tagged with this specific party that received comparably large number of comments emerge as rather mixed in terms of content and messages. For instance, the video Morna Jensen! had reached 267 comments at the time of data collection — a comparably large number in the Norwegian context. Apparently uploaded by famed Norwegian lifestyle blogger Sophie Elise Isachsen , the video features disco music while Isachsen and others pose and dance, and while captions detail some of the more controversial political decisions and utterances made by representatives of the Progress Party during the previous parliamentary period. At the time of this writing, the top comments (as in the most liked comments) appeared to feature a plethora of hate speech — ranging from sexist remarks about Isachsen to a variety of racial slurs, sometimes combined with utterances supporting the Progress Party.
As such, while the video itself featured content negative to the Progress Party, would-be supporters of said party appeared to be readily at hand for engaging in what appears to be mostly hateful, misogynist and xenophobic commenting activity — as well as in liking such comments. At least in this case, while liking the video could be seen to function as an utterance of support for the sentiments expressed within it, the comments yielded do indeed feature some very different points of view. These results, and the example provided above, could be seen as in line with tendencies for other online services to essentially become ‘hijacked’ by right-wing supporters (Bruns and Highfield, 2013; Larsson, 2014). With our current case in mind, it would seem that while a comparably small group of supporters of right-wing parties might feel inclined to partake by means of commenting, those critical of such parties are apparently more motivated to show their disapproval by means of the ‘dislike’ button. Perhaps this apparent unwillingness to engage with political opponents by means of commenting could be related to fear of online harassment. Future research might be able to shed more light on these issues.
Next, for the influences of Likes and Dislikes on the number of views of YouTube videos, Table 3 features a setup similar to the previous one.
Table 3: Multiple regression analyses analysing the influences of Likes and Dislikes on views of YouTube videos.
Notes: Results presented for each individual party. Standardized beta values presented, *p < 0.05; **p < 0.01; ***p < 0.001.
Ap Frp H Krf MDG R Sp Sv V Likes .14** .05 .33*** .08 -.02 .46*** .26** .31** .19** Dislikes .60*** .15 .13* .09 .33*** .29*** .42*** .24* .46*** R2
While Table 2 suggested that the Like functionality appeared as more influential than the Dislike variety in relation to commenting activity, the results presented in Table 3 indicate somewhat differing tendencies for the number of views yielded. Among the significant beta values reported, four such instances featured more sizable values in relation to the Dislike functionality (for Ap, MDG, Sp and V), while three parties emerged as having the more positive Like functionality yielding comparably more influence over view rates (H, R and Sv). While we should not make overtly strong statements about causality, these results would seem to indicate that in comparison to commenting, viewing rates emerge as more clearly positively correlated with the Dislike functionality. This appears especially true in relation to the Labour Party (Ap), as the beta value reported in relation to Dislikes for the specified party suggests. As an example of videos with high number of views that had been tagged as to indicate content pertaining to the Labour Party, we can point to a video uploaded by the Norwegian tabloid Dagbladet, featuring a debate regarding immigration with participating representatives from the Labour Party, Progress Party and Liberal Party. The video , labelled by the uploading newspaper as an “intense immigration debate” (author’s translation from Norwegian to English), does indeed feature engaged exchanges between the three politicians and the two journalists functioning as debate chairs — a characteristic of the debate that is clearly mirrored in the comment fields. While we do not see the same type of atrocities being uttered here as in the previous example, the most liked comments appear as largely supportive of the Frp representative — controversial Minister of Migration and Integration Sylvi Listhaug — and rather critical of her political opponent as well as of the journalists guiding the debate.
In sum, while commenting on YouTube videos appears as related to the more positive Like response, a similar steadfast claim not be made with regards to the number of views yielded by each video. To be precise, for this latter category, a small majority of the significant results reported in Table 3 suggests that Dislikes can function to raise view statistics. For both comments and views, the analyses showed that the right-wing populist Progress Party emerged as comparably successful as their apparent supporters had a rather large presence in the comment fields of the exemplified most commented and most viewed videos.
Discussion and conclusions
While Time’s ‘Person of the Year’ features might not be the most precise way to capture societal tendencies, these and other cover stories can certainly function as indicators of the current zeitgeist of society. Case in point: on 20 August 2016, a tweet originally posted by journalist and media consultant Jim Long began to rise to the top of the ‘trending’ charts generated by Twitter traffic. The tweet featured the by-now famous front cover of Time’s December 2006 issue, exclaiming the person of the year to be ‘You’. Explaining the rationale of the editors, Lev Grossman put forth that the award was “about the cosmic compendium of knowledge Wikipedia and the million-channel people’s network YouTube and the online metropolis MySpace” (Grossman, 2006). In the aforementioned tweet, the image of the cover featuring the caption ‘Yes, you. You control the information age. Welcome to your world.’ was juxtaposed with a cover from the same magazine, published some 10 years later, in August of 2016. Displaying a troll-like character typing away on a laptop computer, the caption of this latter cover read ‘Why we’re losing the Internet to the culture of hate’ (Stein, 2016). Stating “What a difference ten years makes” , the tweet, which succeeded to gain a certain level of attention, thus provided a somewhat cynical way of summing-up what could perhaps be referred to as an increasingly critical view of online discussion and participation that has grown more common over the last decade. Granted, while Grossman’s original piece reflected on issues of hate speech, suggesting that “[...] some of the comments on YouTube make you weep for the future of humanity just for the spelling alone, never mind the obscenity and the naked hatred” (Grossman, 2006), the overall rhetoric of the 2006 article — as well as of many then-contemporary offerings — were largely dominated by optimistic views regarding the role of the Internet. This study, then, has expanded on previous research efforts that have attempted to empirically assess the potentials of a variety of online media — efforts that have, more often than not, presented findings indicating a variety of difficulties to be associated with the uses of online media for political purposes. Indeed, while not all such difficulties have been associated with the patterns uncovered here, the results presented here seem to resonate with a current popular understanding of issues pertaining to online participation and discussion.
While the findings presented here have illuminated some of the apparent mechanisms influencing YouTube prowess, they have also provided some interesting discrepancies that deserve further attention. For instance, as shown in Table 2, the number of Likes received by a specific video emerged as a comparably more successful gauge for comments made than the number of Dislikes yielded. One possible interpretation of these findings could have to do with previous findings regarding online activity relating to the Progress Party. Specifically, as the party at hand appears to have enjoyed considerable online support on Facebook (Larsson, 2016), and as issues typically brought to the fore by their representatives — often relating to immigration — result in considerable amounts of activity on Norwegian newspaper Facebook Pages (Larsson, 2017a), we should not perhaps not be too surprised at their rate of success on the platform under scrutiny here as well. As such, while a silent majority might click like buttons in relation to a video critical of the Progress Party, the comments posted tell another story altogether — thanks to what appears to be ardent Progress Party supporters. While not necessarily formally related to the party under discussion, these commentators nevertheless succeed in setting the tone for the comment field of the video used as example — a tone, then, that is not necessarily concurrent with what one would perhaps assume given the statistical relations reported in Table 2, and that should be studied further.
As for influences on the number of views of YouTube videos, the results presented in Table 3 provided a different imagery when compared to the findings related to commenting activity. While the size of the reported coefficients varied, the overall tendency here appears to be that higher view counts are primarily related to higher counts of dislikes. In a more general sense, this finding could be seen as related to our previous discussion regarding hate and anger as a driver of online activity and popularity. As for our specific theme, the uncovered relationship between an indicator of negative emotion and the popularity of a video could be seen as symptomatic of the often-discussed decline in political interest and party association (e.g., Karlsen and Skogerbø, 2015) — perhaps also of a more general tendency for increasing scepticism or even contempt for politicians.
While “one cannot imagine any party not utilising YouTube” , political actors are indeed not alone in their utilization of the studied platform. Granted, while professionalized political organizations might have plenty of resources at hand to produce “slick, professionalized televisual political communication” , such online offerings are not necessarily those that yields the most search hits or indeed succeeds in ‘going viral’. As shown in the current study, videos that reach comparably higher levels of popularity do not necessarily carry the mostly balanced tone of political statements and ‘spots’ that are commonplace in the Norwegian context. Strong emotions rule, and the stand-out role of the right-wing populist Progress Party is as clear on YouTube as it has been shown to be on other platforms, such as Facebook.
While the results presented here have provided important insights into the drivers of popularity on YouTube in the setting of political communication, the design employed needs to be complemented with further research in order to gain more in-depth understandings of these processes. One way forward could be to focus specifically on the comments made in relation to politically themed videos, expanding on the findings provided here. Such an attempt could perhaps also expand beyond the platform examined here, utilizing some form of cross-media comparative approach (as recommended by Esser and Hanitzsch, 2012; Felt, 2016; Jungherr and Theocharis, 2017). Such an approach could increase our understanding of how political discussion might shift from one platform to another. Relatedly, it would be interesting to see how the resuilts presented here compare to findings yielded from some other thematic context. Researchers with other thematic interests might find it useful to build on the work presented here when studying drivers of online popularity in other settings than during elections.
Another opportunity for research in this vein could be to focus on how political actors — parties, politicians — handle the negativity expressed in the comment fields related to their YouTube and other online presences. For media organizations, such comments are sometimes seen as problematic only if they are posted on the main Web site, which could raise a series of legal issues. Problematic comments posted on organizational social media sites, however, are seen as drivers of traffic since they often fall outside the judicial context within which a non-U.S. organization operates (e.g., Braun and Gillespie, 2011). The same tendencies should be interesting to uncover further also for scholars focusing on political communication. What efforts, if any, are undertaken by political actors to curate and perhaps even ‘clean’ the comment fields provided in relation to their social media presences? While such actors might not be personally liable for any hate speech or slander found in their related comment fields, the assumption could be made that they would supposedly nevertheless seek to keep them in a representative state. Altogether, these findings and suggestions for future efforts speak to the problems often associated with interaction between citizens and political actors — an issue that has been a fixture in this domain of research for some time (e.g., Stromer-Galley, 2000) and that does not seem to fade away from public as well as academic interest.
About the author
Anders Olof Larsson is Professor at the Westerdals Institute for Communication and Design, Kristiania University College (Oslo, Norway).
E-mail: anders [dot] larsson [at] westerdals [dot] no
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Received 7 March 2018; accepted 6 June 2018.
“Thumbs up, thumbs down? Likes and dislikes as popularity drivers of political YouTube videos” by Anders Olof Larsson is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Thumbs up, thumbs down? Likes and dislikes as popularity drivers of political YouTube videos
by Anders Olof Larsson.
First Monday, Volume 23, Number 8 - 6 August 2018