DNVA and Intratextual Analysis
In chapter 10 of The Discourse of News Values we suggest that it would be useful to consider where in a news item news values are constructed. Bell (1991), for example, notes the importance of story order (80– 81) as well as position within the lead paragraph (176), and Jucker (1996: 383) shows that the most explicit mentions of news actors and claims to their newsworthiness are made in the lead. Such intratextual concerns could be addressed through combining discursive news values analysis (DNVA) with analysis of genre structure in the analysis of complete texts.
We briefly examine one example hard news story here from The Guardian (Australian edition), which was first published on 31 December 2016. Our analysis focuses on the construction of news values in relation to generic structure.
Headline: Qantas: hundreds of passengers stranded in Dubai over New Year’s
[You can download your own copy of this analysis here: Genre analysis Qantas Story 31 Dec 2016]
Generically, the story consists of the nucleus (headline, sub-headline, image, caption, lead) and five satellites (1 Cause-and-effect; 2 Contextualisation; 3 Appraisal; 4 Cause-and-effect; 5 Cause-and-effect).
The following abbreviations for the news values have been used in this table.
Key:
E = Eliteness
I = Impact
N = Negativity
Pers = Personalization
Pos = Positivity
Prox = Proximity
S = Superlativeness
T = Timeliness
An intratextual DNVA of this hard news story could focus on analysis of news values in the different generic stages of the story. The nucleus, for example, constructs all of the news values one expects in a hard news story: Negativity, Superlativeness, Impact, Timeliness, and because it mentions ordinary passengers/customers, Sydney, Australia and an iconic well-known Australian company (Qantas), it also constructs (weak) Personalization, Proximity and Eliteness. Juxtaposing this, in the image we have Aesthetic Appeal constructed through an impressive sunset casting a warm orange glow over the airfield and Qantas jet, and sparkling sunlight reflections glinting off the surfaces. This contrast in the construction of news values in different semiotic modes (beauty in the image and negativity in the language) is a phenomenon that we have previously encountered in our research on news values. The construction of so many different news values in the nucleus also confirms what linguists know about the generic structure of hard news stories, where the nucleus represents the topic as maximally newsworthy or establishes the news values angle.
We could also compare different parts of the text for the construction of a particular news value, for example, Personalization. In satellites 3 and 4, individual, named passengers share their direct experiences of the delays, thus clearly constructing Personalization. However, in the remainder of the text (in the nucleus and satellites 1, 2 and 5) only generic references are made to passengers/customers, constructing very weak Personalization. The use of more generic labels for passengers assists in being able to quantify the number of people affected (hundreds), which constructs Superlativeness. Without going into detail here, what is also interesting in terms of generic structure and news values, is that there are two related events that are constructed as newsworthy: The majority of the story (nucleus and satellites 1, 3, 4, 5) is about establishing the stranding of the Qantas plane as newsworthy, while satellite 2 focuses on a simultaneous event as point of comparison (Contextualisation), constructing the delay by fog of other planes at Dubai as newsworthy. Satellite 2 also shows that not all elements of the verbal text establish newsworthiness, as the sentence starting with High humidity and ending with peninsula simply explains the cause of the fog.
Another interesting intratextual pattern that can be observed in this story is the very close relations between the constructions of news values in the verbal elements making up the nucleus. The headline (Qantas: hundreds of passengers stranded in Dubai over New Year’s) and lead (Hundreds of Qantas passengers spent New Year’s Eve stranded in Dubai…) are very close reformulations of each other, and thus construct the same news values of Negativity, Superlativeness, Timeliness, cultural Proximity/Eliteness, and weak Personalization. Again, this is typical of hard news story structure, and confirms that headlines are usually derived from the lead paragraph. Interestingly, we can observe similar phenomena between the second clause of the lead (…after their flight to Sydney was delayed by more than 20 hours) and the image caption (has been delayed for at least 20 hours in Dubai, en route to Sydney), and also between satellite 1 (Engineers in Dubai worked on the A380 aircraft while passengers were put up in hotels while they waited to learn when they could fly to Australia) and the sub-headline (Engineers trying to fix A380 aircraft as Qantas customers are put up in hotels while they wait to learn when they will get to Australia), which thus construct the same news values. All of these are clear examples of intratextual repetition and reinforcement of news values, as the text develops.
The image and its caption, however, relate quite differently and only vaguely to each other. The only commonality seems to be that the caption includes the nominal group a Qantas A380 aircraft, while the image clearly shows a Qantas plane (with the logo visible) – hence both modes construct cultural Proximity/Eliteness. But while the caption text does what many news image captions do, in pointing to the newsworthiness of the event (delayed for at least 20 hours in Dubai, en route to Sydney), the actual plane is only generically depicted and labelled in the image/caption, thus making it unclear whether the plane depicted is the one that has been delayed. The image hence behaves much more like a stock image than as a news image: The verbal deixis a Qantas A380 aircraft of the caption text along with the unidentifiable background in the image (there is no distinguishing feature in the image to suggest that this is Dubai airport or that the aircraft depicted has a mechanical problem) do nothing to disambiguate the image, as specifically emanating from this news event.
Analysis of both news values and attribution provides further insights (c.f. Bednarek 2016): Roughly half of this story consists of attributed text, including by sources established as ‘ordinary’ Australians (satellites 3-4) and by a source established as ‘elite’ (in satellite 5). Thus the story gives a voice to those affected before integrating the airline’s response. Satellites 3-4, which focus on passengers’ negative experiences and emotions, primarily construct Personalization, Negativity, Timeliness, and Proximity. Satellite 5 establishes Eliteness, Proximity and Timeliness. Other content attributed via indirect discourse, from UAE’s National Center of Meteorology & Seismology (Eliteness), occurs in satellite 2 and establishes Negativity and Superlativeness. Direct discourse is only used for the Australian sources (passengers, friends of passengers, Qantas).
Finally, we could also apply intratextual DNVA through analysis of the multimodal packaging of this story (as we do for other stories in our book). As a whole, the verbal text in this story constructs the news values of Proximity, Negativity, Personalisation, Timeliness, Superlativeness, and Eliteness. Impact is mainly implied, i.e. most of the examples coded as Negativity are indirectly also examples of Impact. The image constructs Aesthetic Appeal and cultural Proximity/Eliteness. Given the generic nature of the image (discussed above), this photograph behaves much more like a stock photograph than a news image. Thus the image functions more to attract readers to the story (through a striking image) and can be read as an illustration/example of the sort of plane that was at the centre of this story.
In sum, an intratextual analysis focuses on bringing together the analysis of textual development (for instance, genre structure, cohesion, etc) with the analysis of newsworthiness, providing in-depth insight into how news values are distributed within texts, and thus revealing the shapein which events are semiotically ‘packaged’ for news consumption by audiences.
References
Bednarek, M. (2016). ‘Voices and values in the news: News media talk, news values and attribution’, Discourse, Context & Media 11: 27–37.
Bell, A. (1991). The Language of News Media. Oxford: Blackwell.
Jucker, A. H. (1996). ‘News actor labelling in British newspapers’. Text 16(3): 373–390.
Feez, S., Iedema, R., and White, P. R. R. (2008). Media Literacy. Surry Hills, NSW: NSW Adult Migrant Education Service.
White, P. R. R. (1997). ‘Death, disruption and the moral order: The narrative impulse in mass “hard news” reporting’. In F. Christie and J. R. Martin (Eds.). Genres and Institutions: Social Processes in the Workplace and School, 101– 133. London: Cassell.
How to cite this page and genre/news values analysis table:
PAGE:
Caple, H. and Bednarek, M. (2017) ‘DNVA and intratextual analysis’. Discursive News Values Analysis (DNVA). http://www.newsvaluesanalysis.com/our-book/extensions/dnva-and-intratextual-analysis/
ANALYSIS TABLE:
Caple, H. and Bednarek, M. (2017) ‘Genre and news values analysis of Qantas story 31 Dec 2016’. Discursive News Values Analysis (DNVA). http://www.newsvaluesanalysis.com/our-book/extensions/dnva-and-intratextual-analysis/