I started my PhD with this question in mind. The reason was this example.
I started my PhD with this question in mind. The reason was this example.
Application: Coverage of protest events over time
I started my PhD with this question in mind. The reason was this example.
Application: Coverage of protest events over time
Idea: Analyse the framing of a story instead of its content
I started my PhD with this question in mind. The reason was this example.
I collected coverage containing reports about domestic protest from 26 UK newspaper. The topics of the protests differ wildly. Between fox-hunting protests, Anti-war protest, high fuel prices and pro- and anti-Brexit protests.
We all use framing to make sense of everyday events and issues when telling others about it. Example: Campus West end: We can either tell people about the modern architecture blending in with the style of the old buildings; the bright rooms, modern teaching facilities, that the campus is adjacent to a beautiful park and that is nice food available on campus. Or we can tell people that it's almost impossible to live close to campus since it is located in one of the most expensive neighbourhoods in the city, that there are no cheap places nearby where you can eat or drink (tying students to the expensive and sometimes low quality food in the Mensa) and that there are not enough power outlets in the offices. None of these facts are untrue, but based on the selection of information, you can tell completely different stories
"To frame is to select some aspects of a perceived reality and make them more salient in a communicating text, in such a way as to promote a particular problem definition, causal interpretation, moral evaluation, and/or treatment recommendation for the item described" (Entman, 1993, original emphasis).
→ focus only on in-depth description
→ hard to ensure validity and reliability
→ easier to code = more validity and reliability
→ make analysis scalable but same concept?
Qualitative approaches
→ focus only on in-depth description
→ hard to ensure validity and reliability
→ easier to code = more validity and reliability
→ make analysis scalable but same concept?
Qualitative approaches
"To frame is to select some aspects of a perceived reality and make them more salient in a communicating text, in such a way as to promote a particular problem definition, causal interpretation, moral evaluation, and/or treatment recommendation for the item described" (Entman, 1993, original emphasis).
"To frame is to select some aspects of a perceived reality and make them more salient in a communicating text, in such a way as to promote a particular problem definition, causal interpretation, moral evaluation, and/or treatment recommendation for the item described" (Entman, 1993, original emphasis).
Case/population: Mainstream news media articles about protests in the UK (1992-2017)
Time-series design: it is expected that the patterns have changed substantially since the first seminal studies – not least due to the arrival of the internet (Cottle, 2008)
Data: Population scale sample of protest reports in newspapers (n > 27,000)
State of knowledge: Journalists use a default theme (so called protest paradigm) to report about protest: details about the event (clash with police, the appearance of protesters, nuisance caused or reactions of bystanders) are highlighted while the message of protesters is undermined or not even mentioned.
Frame elements are further divided into coding variables:
Frame Element | Variable | Code | Description |
---|---|---|---|
Problem Definition | Topic | Event | Description of the event (e.g., size, marching route or what protesters did) but not highlighting th... |
Problem Definition | Topic | Spectacle | Highlighting the entertaining or spectacle aspects (emptying protest of its political significance). |
Problem Definition | Topic | Violence/Crime | Violence, vandalism and destruction of public or private property surrounding a protest. |
Problem Definition | Topic | Clash | Confrontation with the police, not necessarily violent. |
Problem Definition | Topic | Protesters | The appearance, mental ability, visual deviance and oddities of the protesters (including pathologis... |
Par_ID | Problem Definition: Topic: Violence/Crime | Problem Definition: Actor: Police | Moral Evaluation: Benefit: Reinstating public order | Moral Evaluation: Risk: Public safety | Causal Attribution: Risk_Attribution: Protesters | Causal Attribution: Benefit_Attribution: Police | Treatment: Judgement_Positive: 0 | Treatment: Judgement_Positive: 1 | Problem Definition: Topic: Nuisance | Problem Definition: Topic: Protesters | … |
---|---|---|---|---|---|---|---|---|---|---|---|
14900405 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
The R package NbClust (Charrad et al., 2014) combines many indices to determine optimal cluster solutions:.
"ch" (Calinski and Harabasz 1974) "duda" (Duda and Hart 1973) "pseudot2" (Duda and Hart 1973) "cindex" (Hubert and Levin 1976) "gamma" (Baker and Hubert 1975) "beale" (Beale 1969) "ccc" (Sarle 1983) "ptbiserial" (Milligan 1980, 1981) "gplus" (Rohlf 1974; Milligan 1981) "db" (Davies and Bouldin 1979)
Heatmap showing cluster means for codes:
model | Accuracy | AccuracyLower | AccuracyUpper | package |
---|---|---|---|---|
Maximum Entropy | 0.64 | 0.44 | 0.81 | RTextTools |
SVM | 0.59 | 0.39 | 0.78 | quanteda.classifiers |
LogitBoost | 0.59 | 0.36 | 0.79 | caret/caTools |
bagging | 0.50 | 0.31 | 0.69 | RTextTools |
Naive Bayes | 0.48 | 0.29 | 0.68 | quanteda |
Random Forest | 0.48 | 0.29 | 0.68 | caret/ranger |
NNSEQ | 0.44 | 0.25 | 0.65 | quanteda.classifiers |
Penalised Multinomial Regression | 0.44 | 0.25 | 0.65 | glmnet |
Work in progress (training/test sample n = 270/30)!
Once this is done, we can show change over time and do some analysis why certain reports are the way they are (right wing protest, more positive reports from right-wing media?)
bit.ly/JBGruber_framing_paper
Johannes B. Gruber
Data downloaded from LexisNexis using "protest" and "demonstration" (plus several variations) before cleaning the data:
I started my PhD with this question in mind. The reason was this example.
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