RESUMEN DE LAS CARACTERISTICAS GENERALES DE LOS MGAMC A ESCALA MUNDIAL

The TONA respondents used positive Impact to evaluate the personalised stories embedded in the news texts:

Text Box 6.2 Instances of positive Impact by TONA respondents

Examples 6.1 and 6.2 show two instances of how the TONA respondents evaluated the use of personalisation in the news texts. In example 6.1, respondent A14 evaluated a quotation from one news actor: a doctor working in Gaza. The respondent stated that the doctor’s

[6.1] ‘I think also (.) the doc- tor eh I think his (2) I can’t find where it is now I think it might be below [reading article] yeah I think it’s towards the end but yeah I think the doctor’s experience is quite eh (.) strong as well cause I think he just says about civilian casualties and how horrific can’t find it now but I think he uses quite strong language about the eh (.) about the scenes so I think they’re the main voices’ (A14)

[6.2] ‘scenes of panic (.) fleeing (.) killed (.) these are all words that they’re quite eh (2) they all fit that idea of death so and they’re quite visual aren’t they eh (.) they invoke like images for you I think that’s (1) especially for yeah for that bit where they’re talking about who exactly is being affected (A15)

ATTITUDINAL READER RESPONSE TO NEWS TEXTS

146 language was ‘strong’, specifically referring to the news text through the use of the word ‘language’. The evaluation ‘strong’ suggests that the doctor’s quotes were engaging to the respondent. In example 6.2, respondent A15 does not refer to a specific news actor, but instead suggests that the words used by the reporter ‘invoke images’. This was categorised as positive Impact as it suggests that the words were so engaging and ‘dramatic’ that the respondents was able to picture the scene (Martin & White 2005: 56). The respondent went on to specify that this evaluation was especially true for the parts of the news text that described ‘who exactly’ was affected. This suggests that personalised aspects of the news texts were more impactful to this respondent than general descriptions.

While the TONA respondents focused on the language used for personalisation, the LB respondents used positive Impact to evaluate the use of different media to construct personalised news perspectives:

Text Box 6.3 Instances of positive Impact by LB respondents

In example 6.3, respondent LB12 referred to the Tweets embedded in the LB as ‘powerful’, specifying that the Tweets from ‘civilians’ were the especially engaging. Similar to the evaluations made by TONA respondents, this again suggests that stories about specific

[6.3] ‘I think the tweets overall are just (.) they’re so powerful like you know especially from the civilians perspective they’re so powerful for giving you like you know a real a much more real time sense of (.) at the right time (.) a much more like brutally real sense of what’s going on’ (LB12)

[6.4] ‘one of his like neighbours speaks about him a bit (.) which is (.) eh (.) interesting cause it (.) makes him more like a real people instead of kind of a (.) just a a shooter he’s actually someone’s neighbour and someone’s parent perhaps you know (.) eh (1) and that picture of him is very chilling’ (LB22)

[6.5] ‘this would give you a bit more detail than perhaps you would look for (3) but the way it’s sort of integrated all the social media stuff is quite interesting (.) you can kind of see lots of different people’s opinions all within one news article which you normally can’t do’ (LB23)

ATTITUDINAL READER RESPONSE TO NEWS TEXTS

147 individuals and civilians are more engaging than other parts of the news texts. Respondent LB12 also evaluated the Tweets as ‘real’, which was found in half of the LB respondents’ evaluations of Tweets. The respondent intensified this statement using the adverb ‘brutally’. This suggests that the Tweets were perceived as realistic even though the respondents, nor myself, were unable to confirm the authenticity of these Tweets. Example 6.4 shows respondent LB22’s evaluation of the picture of the shooter included in the LB. They evaluated the picture as ‘very chilling’, invoking an affective evaluation of fear in response to the inclusion of a different medium: photography. Respondent LB23 in example 6.5 evaluated the use of social media more generally, stating that it was ‘interesting’. While this does invoke Affect: ‘I am interested in this’, it conveys a less emotional response than evaluations such as ‘chilling’. The use of the term ‘interesting’ suggests a detachment of the respondent from the news event who instead focused on the evaluation of the text and how the Tweets were ‘integrated’. Each of the respondents used positive Impact to evaluate the use of different voices within the news texts, specifically referring to individuals whose quotes were presented in the news texts. This suggests that personalisation of news stories can increase the use of positive Impact in respondents’ evaluations of the news texts. Respondents seemed to use consistently positive evaluations of what were perceived to be ordinary voices in news texts, regardless of the presentation of these voices.

Bednarek and Caple (2014) state that ‘quotes from ‘ordinary’ people’ can increase the news value personalisation. This is consistent with my results that show that the higher frequencies of positive Impact in the evaluations of LB respondents may relate to the construction of personalisation (Bednarek & Caple 2014). With the inclusion of Tweets, pictures and videos, the LBs constructed more personalisation than the TONAs (see Chapter Five). The Tweets in the LBs are fulfilling this goal, giving readers quotes from ordinary people, seemingly without editing or interference from the journalists. The construction of personalisation in news texts has been found to increase audience numbers for news texts

ATTITUDINAL READER RESPONSE TO NEWS TEXTS

148 suggesting that readers positively respond to news texts that include personalisation (Schaudt & Carpenter 2009).

In addition to evaluations of personalisation, TONA respondents used positive Impact to evaluate the style and descriptions in the news texts:

Text Box 6.4 Instances of positive Impact evaluating the style of the TONAs

In examples 6.6 and 6.7, the respondents used evaluative adjectives to describe the word choice and descriptions used in the news texts. Respondent A13 evaluated the information about the numbers of victims as ‘graphic’ and respondent A14 evaluated one section of the news text as ‘almost storytelling’, ‘dramatic’ and ‘descriptive’. Both respondents specifically referred to the news text as opposed to the news event, they stated ‘it said’ and ‘it’s trying to paint a picture’. Word choice and style was not evaluated using Impact by the LB respondents who instead focused their Impact evaluations on the use of different media. In example 6.8, respondent A21 made a similar, more invoked evaluation as they said they could ‘visualise’ the situation which created a ‘big impact’. While these respondents did not explicitly use Affect, affective Impact evaluations such as ‘graphic’, ‘dramatic’ and ‘big impact’, invoked Affect. This suggests that the numbers of victims and descriptions used in the TONAs were

[6.6] ‘I think that it like (.) it is-is really emotive when it talks about - it is like what I said it’s graphic about the dead bodies and it says about schools and it mentions number of who were k- of how many people were killed’ (A13)

[6.7] ‘there’s this bit where it says at the scene and it’s trying to paint a picture like it’s almost storytelling that means things are quite dramatic so when he’s like the thick black column of smoke and it’s descriptive but again it is painting eh (.) a certain scene’ (A14)

[6.8] ‘I think when it says (.) when the shooter was standing in the classroom when he asked (.) what religion they were and he was shooting some people and then it’s just like bodies on the floor (.) and that was just so I could visualise it so that was a big impact there’ (A21)

ATTITUDINAL READER RESPONSE TO NEWS TEXTS

149 engaging to the respondents, causing them to ascribe affective characteristics to these news texts.