OpenFraming: We brought the ML; you bring the data. Interact with your data and discover its frames

08/16/2020
by   Alyssa Smith, et al.
0

When journalists cover a news story, they can cover the story from multiple angles or perspectives. A news article written about COVID-19 for example, might focus on personal preventative actions such as mask-wearing, while another might focus on COVID-19's impact on the economy. These perspectives are called "frames," which when used may influence public perception and opinion of the issue. We introduce a Web-based system for analyzing and classifying frames in text documents. Our goal is to make effective tools for automatic frame discovery and labeling based on topic modeling and deep learning widely accessible to researchers from a diverse array of disciplines. To this end, we provide both state-of-the-art pre-trained frame classification models on various issues as well as a user-friendly pipeline for training novel classification models on user-provided corpora. Researchers can submit their documents and obtain frames of the documents. The degree of user involvement is flexible: they can run models that have been pre-trained on select issues; submit labeled documents and train a new model for frame classification; or submit unlabeled documents and obtain potential frames of the documents. The code making up our system is also open-sourced and well-documented, making the system transparent and expandable. The system is available on-line at http://www.openframing.org and via our GitHub page https://github.com/davidatbu/openFraming .

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 5

11/24/2021

Detecting Frames in News Headlines and Lead Images in U.S. Gun Violence Coverage

News media structure their reporting of events or issues using certain p...
04/19/2021

Modeling "Newsworthiness" for Lead-Generation Across Corpora

Journalists obtain "leads", or story ideas, by reading large corpora of ...
04/05/2018

Few-Shot Text Classification with Pre-Trained Word Embeddings and a Human in the Loop

Most of the literature around text classification treats it as a supervi...
02/14/2022

Semantic Matching from Different Perspectives

In this paper, we pay attention to the issue which is usually overlooked...
11/28/2019

KPTimes: A Large-Scale Dataset for Keyphrase Generation on News Documents

Keyphrase generation is the task of predicting a set of lexical units th...
04/22/2021

Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames

Understanding how news media frame political issues is important due to ...
04/12/2021

Semantic Frame Forecast

This paper introduces semantic frame forecast, a task that predicts the ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.