Datasets:

Modalities:
Text
Formats:
json
Languages:
English
ArXiv:
DOI:
Libraries:
Datasets
Dask
License:
emilys commited on
Commit
3edc61c
1 Parent(s): b358e21

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +92 -23
README.md CHANGED
@@ -9,17 +9,84 @@ size_categories:
9
  - 100M<n<1B
10
  ---
11
 
 
 
12
  ![headline_image_with_title.jpg](https://s3.amazonaws.com/moonup/production/uploads/61654589b5ec555e8e9c203a/fJiAy43PFD3FBa1aMSzHz.jpeg)
13
 
14
- ## Dataset Summary
15
- HEADLINES is a massive semantic similarity dataset, containing 396,001,930 pairs of different headlines for the same newspaper article, taken from historical U.S. newspapers, covering the period 1920-1989.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
16
 
17
  ## Dataset Creation
 
 
18
  The dataset was constructed using a large corpus of newly digitized articles from off-copyright, local U.S. newspapers.
19
  Many of these newspapers reprint articles from newswires, such as the Associated Press, but the headlines are written locally.
20
  The dataset comprises different headlines for the same article.
21
 
22
- ## Dataset Description
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
23
  The dataset contains 396,001,930 positive semantic similarity pairs, from 1920 to 1989.
24
 
25
  ![image (3).png](https://s3.amazonaws.com/moonup/production/uploads/61654589b5ec555e8e9c203a/vKeR-SEEfYte6ZZbdpaq3.png)
@@ -29,35 +96,37 @@ It contains headlines from all 50 states.
29
  ![map (1).png](https://s3.amazonaws.com/moonup/production/uploads/61654589b5ec555e8e9c203a/0WMdO8Fo1nfYiId4SlWaL.png)
30
 
31
 
32
- ## Dataset Structure
33
- Each year in the dataset is divided into a distinct file (eg. 1952_headlines.pkl), giving a total of 70 files.
34
 
35
- Each of these contains a list of dictionaries of the form:
36
 
37
- ```python
38
- {
39
- "headline": "...",
40
- "date": "...",
41
- "newspaper": "...",
42
- "state": "...",
43
- "cluster": "..."
44
- }
45
- ```
46
 
47
- ** Headline: headline text.
48
- ** Date: the date of publication of the newspaper article, as a string in the form YYYY-MM-DD.
49
- ** Newspaper: name of the newspaper that published the headline.
50
- ** State: state of the newspaper that published the headline.
51
- ** Cluster: a number that is shared with all other headlines for the same article. This number is unique across all year files.
52
 
53
- We chose to present the dataset in the form of clusters, rather than pairs to eliminate duplication of text data and minimise the storage size of the datasets. Below we give an example of how to convert the dataset into pairs.
54
 
 
 
 
 
 
 
 
 
 
 
 
 
55
 
56
- ## Usage
57
 
58
 
 
59
 
 
 
60
 
61
- ## Contacts
62
  This dataset was created by Emily Silcock and Melissa Dell. For more information, see [Dell Research Harvard](https://dell-research-harvard.github.io/).
63
 
 
 
 
9
  - 100M<n<1B
10
  ---
11
 
12
+ # Dataset Card for HEADLINES
13
+
14
  ![headline_image_with_title.jpg](https://s3.amazonaws.com/moonup/production/uploads/61654589b5ec555e8e9c203a/fJiAy43PFD3FBa1aMSzHz.jpeg)
15
 
16
+
17
+ ## Dataset Description
18
+
19
+ - **Homepage:** [Dell Research homepage](https://dell-research-harvard.github.io/)
20
+ - **Repository:** [Github repository](https://github.com/dell-research-harvard)
21
+ - **Paper:** [arxiv submission](https://arxiv.org/abs/tbd)
22
+ - **Point of Contact:** [Melissa Dell](mailto:melissadell@fas.harvard.edu)
23
+
24
+ ### Dataset Summary
25
+ HEADLINES is a massive English-language semantic similarity dataset, containing 396,001,930 pairs of different headlines for the same newspaper article, taken from historical U.S. newspapers, covering the period 1920-1989.
26
+
27
+ ### Languages
28
+ The text in the dataset is in English.
29
+
30
+
31
+ ## Dataset Structure
32
+ Each year in the dataset is divided into a distinct file (eg. 1952_headlines.pkl), giving a total of 70 files.
33
+
34
+ The data is presented in the form of clusters, rather than pairs to eliminate duplication of text data and minimise the storage size of the datasets. Below we give an example of how to convert the dataset into pairs.
35
+
36
+ ### Dataset Instances
37
+
38
+ An example from the HEADLINES dataset looks like:
39
+
40
+ ```python
41
+ {
42
+ "headline": "FRENCH AND BRITISH BATTLESHIPS IN MEXICAN WATERS",
43
+ "date": "May-14-1920",
44
+ "newspaper": "cuba-daylight",
45
+ "state": "kansas",
46
+ "cluster": 4
47
+ }
48
+ ```
49
+
50
+ ### Dataset Fields
51
+
52
+ - `headline`: headline text.
53
+ - `date`: the date of publication of the newspaper article, as a string in the form YYYY-MM-DD.
54
+ - `newspaper`: name of the newspaper that published the headline.
55
+ - `state`: state of the newspaper that published the headline.
56
+ - `cluster`: a number that is shared with all other headlines for the same article. This number is unique across all year files.
57
+
58
+
59
+ ## Usage
60
+
61
+ [Coming soon]
62
+
63
 
64
  ## Dataset Creation
65
+
66
+ ### Source Data
67
  The dataset was constructed using a large corpus of newly digitized articles from off-copyright, local U.S. newspapers.
68
  Many of these newspapers reprint articles from newswires, such as the Associated Press, but the headlines are written locally.
69
  The dataset comprises different headlines for the same article.
70
 
71
+ #### Initial Data Collection and Normalization
72
+
73
+ To construct HEADLINES, we digitize front pages of off-copyright newspaper page scans, localizing and OCRing individual content regions like headlines and articles. The headlines, bylines, and article texts that form full articles span multiple bounding boxes - often arranged with complex layouts - and we associate them using a model that combines layout information and language understanding. Then, we use neural methods to accurately predict which articles come from the same underlying source, in the presence of noise and abridgement.
74
+
75
+ We remove all headline pairs that are below a Levenshtein edit distance, divided by the min length in the pair, of 0.1 from each other, with the aim of removing pairs that are exact duplicates up to OCR noise.
76
+
77
+ #### Who are the source language producers?
78
+
79
+ The text data was originally produced by journalists of local U.S. newspapers.
80
+
81
+ ### Annotations
82
+
83
+ The dataset does not contain any additional annotations.
84
+
85
+ ### Personal and Sensitive Information
86
+ The dataset may contain information about individuals, to the extent that this is covered in the headlines of news stories. However we make no additional information about individuals publicly available.
87
+
88
+
89
+ ### Data Description
90
  The dataset contains 396,001,930 positive semantic similarity pairs, from 1920 to 1989.
91
 
92
  ![image (3).png](https://s3.amazonaws.com/moonup/production/uploads/61654589b5ec555e8e9c203a/vKeR-SEEfYte6ZZbdpaq3.png)
 
96
  ![map (1).png](https://s3.amazonaws.com/moonup/production/uploads/61654589b5ec555e8e9c203a/0WMdO8Fo1nfYiId4SlWaL.png)
97
 
98
 
 
 
99
 
100
+ ## Considerations for Using the Data
101
 
102
+ ### Social Impact of Dataset
 
 
 
 
 
 
 
 
103
 
104
+ The purpose of this dataset is to widen the range of language and topics for training semantic similarity models.
 
 
 
 
105
 
106
+ This will facilitate the study of semantic change across space and time.
107
 
108
+ Specific biases in the dataset are considered in the next section.
109
+
110
+
111
+ ### Discussion of Biases
112
+
113
+ The headlines in the dataset may reflect attitudes and values from the period in which they were written, 1920-1989. This may include instances of racism, sexism and homophobia.
114
+
115
+ We also note that given that all the newspapers considered are from the U.S., the data is likely to present a Western perspective on the news stories of the day.
116
+
117
+ ### Other Known Limitations
118
+
119
+ As the dataset is sourced from digitalised text, it contains some OCR errors.
120
 
 
121
 
122
 
123
+ ## Additional information
124
 
125
+ ### Licensing Information
126
+ HUPD is released under the Creative Commons CC-BY 2.0 license.
127
 
128
+ ### Dataset curators
129
  This dataset was created by Emily Silcock and Melissa Dell. For more information, see [Dell Research Harvard](https://dell-research-harvard.github.io/).
130
 
131
+ ### Citation information
132
+ Citation coming soon.