AdDownloader：从 Meta 在线广告库自动检索广告及其媒体内容

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2024-10-13 DOI:10.1016/j.softx.2024.101919

Paula-Alexandra Gitu , Roberto Cerina , Stefanie Vandevijvere , Roselinde Kessels

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引用次数: 0

摘要

AdDownloader 是一个 Python 软件包，用于从 Meta 在线广告库下载广告及其媒体内容。有了有效的 Meta 开发人员访问令牌，AdDownloader 就能自动下载相关广告数据，并以用户友好的格式进行存储。此外，AdDownloader 还使用下载数据中的单个广告链接来访问每个广告的媒体内容（如图片和视频），并将其存储在本地。该软件包还提供各种分析功能，例如使用人工智能对广告文本和图片标题进行主题建模，并将其嵌入仪表板中。AdDownloader 可作为命令行界面运行，也可作为 Python 软件包导入，提供灵活直观的用户体验。应用范围从了解在线政治活动的有效性和透明度，到监控不同人群接触有害物质营销的情况。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

AdDownloader: Automating the retrieval of advertisements and their media content from the Meta Online Ad Library

AdDownloader is a Python package for downloading advertisements and their media content from the Meta Online Ad Library. With a valid Meta developer access token, AdDownloader automates the process of downloading relevant ads data and storing it in a user-friendly format. Additionally, AdDownloader uses individual ad links from the downloaded data to access each ad's media content (i.e. images and videos) and stores it locally. The package also offers various analytical functionalities, such as topic modelling of ad text and image captioning using AI, embedded in a Dashboard. AdDownloader can be run as a Command-Line Interface or imported as a Python package, providing a flexible and intuitive user experience. Applications range from understanding the effectiveness and transparency of online political campaigns to monitoring the exposure of different population groups to the marketing of harmful substances.

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.