| --- |
| 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. |
