Datasets:
Tasks:
Text Classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
| annotations_creators: | |
| - expert-generated | |
| language_creators: | |
| - found | |
| language: | |
| - en | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - multi-class-classification | |
| - sentiment-classification | |
| paperswithcode_id: null | |
| pretty_name: Auditor_Sentiment | |
| # Dataset Card for Auditor Sentiment | |
| ## Table of Contents | |
| - [Table of Contents](#table-of-contents) | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| ## Dataset Description | |
| Auditor review sentiment collected by News Department | |
| - **Point of Contact:** | |
| Talked to COE for Auditing, currently sue@demo.org | |
| ### Dataset Summary | |
| Auditor sentiment dataset of sentences from financial news. The dataset consists of several thousand sentences from English language financial news categorized by sentiment. | |
| ### Supported Tasks and Leaderboards | |
| Sentiment Classification | |
| ### Languages | |
| English | |
| ## Dataset Structure | |
| ### Data Instances | |
| ``` | |
| "sentence": "Pharmaceuticals group Orion Corp reported a fall in its third-quarter earnings that were hit by larger expenditures on R&D and marketing .", | |
| "label": "negative" | |
| ``` | |
| ### Data Fields | |
| - sentence: a tokenized line from the dataset | |
| - label: a label corresponding to the class as a string: 'positive' - (2), 'neutral' - (1), or 'negative' - (0) | |
| ### Data Splits | |
| A train/test split was created randomly with a 75/25 split | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| To gather our auditor evaluations into one dataset. Previous attempts using off-the-shelf sentiment had only 70% F1, this dataset was an attempt to improve upon that performance. | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| The corpus used in this paper is made out of English news reports. | |
| #### Who are the source language producers? | |
| The source data was written by various auditors. | |
| ### Annotations | |
| #### Annotation process | |
| This release of the auditor reviews covers a collection of 4840 | |
| sentences. The selected collection of phrases was annotated by 16 people with | |
| adequate background knowledge on financial markets. The subset here is where inter-annotation agreement was greater than 75%. | |
| #### Who are the annotators? | |
| They were pulled from the SME list, names are held by sue@demo.org | |
| ### Personal and Sensitive Information | |
| There is no personal or sensitive information in this dataset. | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| All annotators were from the same institution and so interannotator agreement | |
| should be understood with this taken into account. | |
| ### Licensing Information | |
| License: Demo.Org Proprietary - DO NOT SHARE | |
| This dataset is based on the [financial phrasebank](https://huggingface.co/datasets/financial_phrasebank) dataset. |