ditorea falcidiaz et res ípsaa ad venditorera in falcidian sibí idem venditi.—

- Events and Sources

Only two cases, the horsemeat and poo-meat case, started with one trigger event: a disclosure in the news media about malpractices in meat processing companies. In the poo-meat case journalistic research revealed food fraud and insanitary practices, which we define as a media-generated event. In the horsemeat case, reports from food safety authorities were reported in news media, which we define as a genuine event. The other three cases were characterized by multiple actor-generated events in which the communicative acts of stakeholders instigated peak activity. In the factory farm case the occasion most referred to is a ‘demonstration’ organised by a civil organisation (Megastallennee) and in the booster broiler case it is a ‘campaign’ of an animal welfare organisation (Wakker Dier). In the calf puller case, an open letter of Wakker Dier to the State Secretary and parliamentary questions of the PvdD together generated a first wave of activity. The second and biggest wave in this case started after a farmer launched the ‘Anti Wakker Dier’ Facebook page, creating a new venue for discussion.

Duration in months Average messages per day Proportion of messages in peaks Duration of peak average Duration of peak SD Volume Peak Average Volume Peak SD Increase Rate Average Increase Rate SD

Factory Farms 44 47 40% 1.86 1.06 234 332 5.21 2.94

Booster Broiler 31 142 22% 1.82 1.84 759 747 4.94 1.73

Horsemeat 19 138 23% 2.07 1.32 488 3469 6.67 6.06

Poo-meat 8 44 89% 2.39 2.11 350 1090 8.06 4.50

Calf puller 3 18 77% 3.43 2.44 279 441 10.58 2.07

Table 3.1 Statistics of peak activity

Peak duration, in days 1 2 3 4 5 6 7

Total Number of peaks

106 47 38 11 5 2 9

Average Volume of peak per day

167 260 739 652 359 1094 3902

Average Increase rate of peak

7.0 6.5 7.5 6.9 4.9 7.1 9.3

Table 3.2 Comparison of peaks of different lengths (1 to 7 days)

Note: A peak was defined as a time-period (t) with activity at least 3 times higher than the average of a similar time-period before (t-1) and after (t+1) and classified as a 1, 2, ..., 7-day peak according to which time window had the strongest increase rate.

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back to Table of Contents - Organising Concepts

In all cases the most frequent used concept was a negative term that contained and signified the story (table 3.3, row 2). Each of these terms was used as a rhetorical device, was applicable to many situations as an organising concept, and implied a strong moral evaluation. Moreover, in each case, it was used as a hashtag term to indicate what was at stake.

- Issues and Identity Frames

Looking into the issue- and identity-frames, several patterns can be identified. ‘Booster broiler’

and ‘factory farm’ are both hyperboles used to problematize industrial agriculture. In the factory farm case the problem was defined on a systemic level (e.g. ‘public health’, ‘environment’, ‘animal welfare’) and in the booster broiler the attention focussed on sentiments about animal welfare (e.g.

‘limp’ or ‘miserable’ chicken). In both cases, citizen-consumers were called to action for confronting the actors who were held responsible: politicians and retailers respectively.

The calf puller issue was not so much about the industrial system, but about farming practices more specifically. However, farmers were not portrayed as the culprit, but the state secretary for not enforcing the law. Still, farmers counteracted using identity frames, turning the discussion about the issue into a conflict between farmers and animal welfare activists (in the second peak, actors and identity-frames are more frequent and central in the semantic network).

The problem in the horsemeat and poo-meat case was mainly about the lack of transparency in the meat processing sector. In both cases the trigger event was linked to other events and thus became part of a news theme about ‘food scandals’. However, most attention went out to identify the culprit in each case, for which ‘research’ was needed. The horsemeat case was mainly framed as a ‘scandal’

of the industry and the poo-meat case as ‘fraud’ of a company.

Interaction of Actors

In comparison to the benchmark of January 2014 (Y. Y. Liu, Kliman-Silver, & Mislove, 2014), cases of peak social media activity had a high level of retweets (46%, in comparison to 27%) as an indication of amplification; the diffusion of uniform information. The proportion of person-to-person communication through replies and mentions was average (23%, in comparison to 24%), suggesting that the level of exchange increases proportional to the level of activity.

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Table 3.3 Frames of events, issues and actors in each case

Note: In the calf puller case, the 1st and 2nd wave are differentiated.

Factory Farms Booster Broiler Horsemeat Poo-meat Calf Puller Organising

concept

‘Factory Farms’ ‘Booster Broiler’ ‘Scandal’ ‘Fraud’ ‘Anti Wakker Dier’

Event

Who started this? Megastallennee, but also other actors that

No call to action No call to action 1) State Secretary:

enforce the law

Victim ^{Livestock Chickens Consumers Consumers} 1) Animals

2) Farmers Culprit Politicians, regional

and national Supermarkets

and other retailers The Industry.

Secondary the

NVWA, EU NVWA, politics 1) State Secretary 2) You: Farmers

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back to Table of Contents

An analysis of the ten most productive and most addressed accounts and their level of interaction (table 3.4) across cases revealed several patterns. News media accounts were more productive on Twitter, while organisations and groups were more productive on Facebook. The most addressed accounts on Twitter are personal accounts, which were used professionally (profession is mentioned on profile). On Facebook organisational accounts received most reactions. Retailers, more specifically, had high level of posts on Facebook because they responded to critics that addressed them on their fan page. On Twitter retailers were largely absent, but other organisations, such as meat processing companies, political parties, agricultural organisations (such as sector-organisations) and experts were present. This reflects the more professional (politi cal and sectoral) and interpersonal (horizontal) communication on Twitter, in comparison to the vertical exchange between citizen-consumers and organizations on Facebook.

Looking more specifically at the key players across cases, we found that Wakker Dier received most reactions on Facebook in all cases, except for the calf puller case, in which Anti Wakker Dier received most comments. On Twitter various key players (activists, politicians and representatives of sector organisations) were active in all cases, which indicates an extensive contestation about livestock production, with leaders particularly on the side of animal welfare advocates.

Based on a case comparison of the most productive and most addressed accounts (top 10 senders and top 10 receivers) on Twitter and Facebook we found the following patterns. In the horsemeat and poo-meat case, news media accounts played a dominant role. Whereas national news media sources were dominant in the horsemeat case, in the poo-meat case sectoral news, NGO’s and persons (representatives of agricultural sector and politicians) also formed key players. Moreover, in the horsemeat case the key players generated a much smaller part of the total number of reactions. This suggests that the poo-meat case had relatively high engagement of stakeholders, and the horsemeat issue was a news item of general public interest. The companies that were offended played a key role in both cases: in the poo-meat case the meat processing company was an active player on Twitter, responding to criticism, in the horsemeat case various retailers that sold products containing horsemeat were criticized on their Facebook page. In the booster broiler and factory farm case, an animal welfare organisation (Wakker Dier) and a citizens organisation (Megastallennee) were active, as well as ‘activists’ on Twitter and ‘persons’ on Facebook. In these cases, the key players also generated high level of reactions, both on Twitter and Facebook suggesting a leading role in activity. In the calf puller case, farmers were most productive and agricultural professional were the most addressed on Twitter, suggesting a high level of engagement of persons involved in livestock farming.

Chapter 3 sent by all ten accounts, divided by total number of messages received by all ten accounts.

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