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