headline_detector
Indonesian Headline Detection Python API
This is a Python library that provides APIs for detecting headlines in textual data, especially on social media platforms such as Twitter. The library utilizes a model that has been developed and trained on a dataset of Twitter posts containing both headline and non-headline texts, with the assistance of journalism professionals to ensure the data quality.
$ pip install headline-detector
Available scenario and the performance
| Model | Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | Scenario 5 | Scenario 6 |
|---|---|---|---|---|---|---|
| Fasttext | 0.8766 | 0.8714 | 0.8793 | 0.8714 | 0.8714 | 0.8661 |
| CNN | 0.9081 | 0.9081 | 0.8950 | 0.8898 | 0.8950 | 0.8898 |
| IndoBERTweet | 0.9895 | 0.9921 | 0.9738 | 0.9580 | 0.9843 | 0.9685 |
All meassured in accuracy
Model Throughput
| Model | Throughput (± Text/seconds) |
|---|---|
| IndoBERTweet | ±1.3 |
| CNN | ±281.60 |
| Fasttext | ±2048.41 |
Tested on Intel i7-6700k and 32GB of RAM.
Usage
Output either 0 (non-headline) and 1 (headline)
from headline_detector import FasttextDetector, IndoBERTweetDetector, CNNDetector
detector = FasttextDetector.load_from_scenario(1)
data = detector.predict_text(
[
"nama kamu siapa?",
"Kapolda Jatim Teddy Minahasa Dikabarkan Ditangkap Terkait Narkoba https://t.co/LD9X6VFaUR",
]
)
print(data) # output: [0, 1]
detector = CNNDetector.load_from_scenario(3)
data = detector.predict_text(
[
"nama kamu siapa?",
"Kapolda Jatim Teddy Minahasa Dikabarkan Ditangkap Terkait Narkoba https://t.co/LD9X6VFaUR",
]
)
print(data) # output: [0, 1]
detector = IndoBERTweetDetector.load_from_scenario(5)
data = detector.predict_text(
[
"nama kamu siapa?",
"Kapolda Jatim Teddy Minahasa Dikabarkan Ditangkap Terkait Narkoba https://t.co/LD9X6VFaUR",
]
)
print(data) # output: [0, 1]
# 0 is non-headline
# 1 is headline
Paper
Coming soon.
Metadata
Release files for headline-detector 1.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| headline_detector-1.0.3.tar.gz | 8.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| headline_detector-1.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.5 kB
Release files / headline_detector-1.0.3.tar.gz
| Download URL | headline_detector-1.0.3.tar.gz |
|---|---|
| Size | 8.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5c888280870ac88a4583d0f90cbeacfacf1779bb44090cc043146502e693f6cb
|
|
BLAKE2b-256 checksum How to use checksums |
cfa9f4f47caa8e5792d11c05f4fd23f5d7e672560d733c5d49c173e6f1340dad
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
|
Release files / headline_detector-1.0.3-py3-none-any.whl
| Download URL | headline_detector-1.0.3-py3-none-any.whl |
|---|---|
| Size | 10.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
59f112916a2ae725930d4258d689a1ef706ef663a6a50a1960a144441bcc2f5a
|
|
BLAKE2b-256 checksum How to use checksums |
b961164a4ab756b7e79409e836b323a78c150aeffedc12399fb2e78dfa5f7fe8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
|