https://github.com/centre-for-humanities-computing/literary_evocation

Contains data of the Ficiton4 corpus and for our experiment on literary sentiment evocation
https://github.com/centre-for-humanities-computing/literary_evocation

implicitness literary-analysis literary-language roberta-model sentiment-analysis

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Contains data of the Ficiton4 corpus and for our experiment on literary sentiment evocation

• Host: GitHub
• URL: https://github.com/centre-for-humanities-computing/literary_evocation
• Owner: centre-for-humanities-computing
• Created: 2024-07-06T06:37:40.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-07-10T12:21:14.000Z (4 months ago)
• Last Synced: 2024-07-11T14:28:56.958Z (4 months ago)
• Topics: implicitness, literary-analysis, literary-language, roberta-model, sentiment-analysis
• Language: Python
• Homepage:
• Size: 22.4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Fiction4 sentiment evocation

Data & code for textual features influence on human sentiment perception in literary texts

## 🔬 Data

|             | No. texts | No. annotations   | No. words  | Period     |

|-------------|-----|------|--------|------------|

| **Fairy tales**     | 3   | 772   | 18,597      | 1837-1847  |

| **Hymns**   | 65  | 2,026 | 12,798       | 1798-1873  |

| **Prose**   | 1  | 1,923 | 30,279         | 1952  |

| **Poetry**   | 40  | 1,579 | 11,576         | 1965  |

We present the **Fiction4 corpus** of literary texts, spanning 109 individual texts across 4 genres and two languages (English and Danish) in the 19th and 20th century.

The corpus consists of 3 main authors, Sylvia Plath for poetry, Ernest Hemingway for prose and H.C. Andersen for fairytales. Hymns represent a heterogenous colleciton from Danish official church hymnbooks from 1798-1873.

The corpus was annotated for valence on a sentence basis by at least 2 annotators/sentence.

Full Fiction4 corpus data in `\data\fiction4_data.json`

We compare this fiction corpus again nonfiction texts (across genres)

The nonlit considered is:

1. EmoBank (from this paper [https://aclanthology.org/E17-2092/](https://aclanthology.org/E17-2092/)), repo [here](https://github.com/JULIELab/EmoBank/tree/master). So these are multigenre sentences. (n=10,062 & range=(1 to 674 toks) & mean_length=87.8 toks)

2. Facebook posts (from this paper [https://aclanthology.org/W16-0404.pdf](https://aclanthology.org/W16-0404.pdf)), repo [here](https://github.com/wwbp/additional_data_sets/tree/master/valence_arousal). So these are facebook posts (multiple sentences)(n=2,895 & range=(2 to 445 toks) & mean_length=86.7 toks)

## 💻 Code

All code for our study on human/model sentiment perception across these corpora is available in this repository, see primarily feature extraction (`get_features.py`) and analysis (`analysis.py`).

Annotator agreement calculation for each subcategory of the Fiction4 corpus is in `/annotation/annotator_agreement.py`