---
license: cc-by-4.0
language:
  - en
tags:
  - finance
  - event-detection
  - financial-news
  - social-media
  - sentivent
  - nlp
pretty_name: SENTiVENT × X Financial Narratives
size_categories:
  - 1K<n<10K
---

# SENTiVENT × X Financial Narratives

A dataset linking financial event annotations from the **SENTiVENT** benchmark corpus with X (Twitter) posts scraped around the same events, used to study how financial narratives propagate from institutional news to social media.

## Dataset Contents

| File | Description | Rows |
|------|-------------|------|
| `data/dataset_event_type.tsv` | SENTiVENT sentence-level annotations with **18 event type** multi-labels | 6,883 |
| `data/dataset_event_subtype.tsv` | SENTiVENT sentence-level annotations with **60 event subtype** multi-labels | 6,883 |
| `data/x_sentivent_master_lowcredit_50each.csv` | X posts scraped for each SENTiVENT event (up to 50 posts/event, filtered for low-credit accounts) | 20,968 |
| `data/x_sentivent_cleaned.csv` | Cleaned subset of X posts used in downstream analysis | 1,917 |
| `data/x_sentivent_event_counts.csv` | Post counts per event after filtering | 93 |
| `data/event_registry_sentivent.csv` | Registry mapping each SENTiVENT event to its X scraping query, WSJ/official doc references, and metadata | 93 |
| `data/type_classes_multilabelbinarizer.json` | Ordered label list for the 18 event type classes | — |
| `data/subtype_classes_multilabelbinarizer.json` | Ordered label list for the 60 event subtype classes | — |

## SENTiVENT Annotations (`dataset_event_type.tsv` / `dataset_event_subtype.tsv`)

| Column | Description |
|--------|-------------|
| `document_id` | Article identifier (e.g. `aal00`) |
| `document_title` | Article filename |
| `sentence_idx` | Sentence position within the article |
| `text` | Sentence text |
| `types_event` | List of event types present in the sentence |
| `subtypes_event` | List of event subtypes (may be multi-label) |
| `types_event_unq` | Unique event types |
| `subtypes_event_unq` | Unique event subtypes |
| `token_cnt` | Token count |
| `event_cnt` | Number of event mentions |
| `dataset` | Split tag (`silver` / `gold`) |
| `labels` | Binary multi-label vector (matches `*_classes_multilabelbinarizer.json`) |

**Event type classes (18):** CSR/Brand, Deal, Dividend, Employment, Expense, Facility, FinancialReport, Financing, Investment, Legal, Macroeconomics, Merger/Acquisition, Product/Service, Profit/Loss, Rating, Revenue, SalesVolume, SecurityValue

## X Posts (`x_sentivent_master_lowcredit_50each.csv`)

X (Twitter) posts scraped using queries derived from each SENTiVENT event. Columns:

| Column | Description |
|--------|-------------|
| `event` | SENTiVENT event identifier |
| `event_label` | Human-readable event label |
| `event_date` | Date of the underlying financial event |
| `thread_source` | Source platform (`x`) |
| `thread_url` | Direct URL to the post |
| `id` | Post ID |
| `parent_id` | Parent post ID (for replies) |
| `author` | X username |
| `body` | Post text |
| `score` | Relevance score assigned during scraping |
| `date` | Post timestamp (ISO 8601) |
| `query_used` | X API search query that retrieved this post |
| `lang` | Language code |
| `record_type` | `post` or `reply` |

## Event Registry (`event_registry_sentivent.csv`)

Maps each event to its scraping metadata:

| Column | Description |
|--------|-------------|
| `event` | Event identifier |
| `event_date` | Date of event |
| `event_label` | Human-readable label |
| `event_type` | SENTiVENT event type category |
| `x_query` | X API query used |
| `x_language` | Language filter |
| `wsj_file` | Linked WSJ article (if any) |
| `official_file` | Linked official document (if any) |
| `analysis_note` | Provenance note |

## Usage

```python
from datasets import load_dataset

# SENTiVENT event type annotations
sentivent = load_dataset("jechen2140/cos-iw-financial-narratives", data_files="data/dataset_event_type.tsv", delimiter="\t")

# X posts linked to SENTiVENT events
x_posts = load_dataset("jechen2140/cos-iw-financial-narratives", data_files="data/x_sentivent_master_lowcredit_50each.csv")
```

## Citation

If you use this dataset, please cite the original SENTiVENT corpus:

```
@inproceedings{jacobs2018economeria,
  title={Economic Event Detection in Company-Specific News Text},
  author={Jacobs, Gilles and Lefever, Els and Hoste, Véronique},
  booktitle={Proceedings of the First Workshop on Economics and Natural Language Processing},
  year={2018}
}
```

## License

Dataset card and X post collection: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).  
Original SENTiVENT annotations are subject to their own license; see the [SENTiVENT project](https://github.com/GillesJ/sentivent_economic_event_detection).