RSS Dashboard

Extract summaries, tags, and sentiment from an RSS feed

How It Works

This tool takes a URL for an RSS feed, and automatically generates tags, text summaries, and sentiment analysis.

Tools Used

  • Scrape RSS – parses an RSS feed, extracting each entry's title and url
  • HTML2Text – converts the main content of an HTML page to plain text
  • Summarizer – creates a summary by extracting topic sentences based on frequency of key terms
  • AutoTag – uses a variant of nlp/LDA to extract keywords.
  • Sentiment Analysis – assigns a sentiment rating from -1 (very negative) to to 1 (very positive).

Source Data

We start by examining the RSS feed, extracting the title and content URL. We then convert the content into plain text and remove the HTML tags. Finally, we extract topic tags, analyze it for sentiment, and generate a meaningful summary.

Takeaway

By wiring up a series of very simple API calls, a developer can quickly scrape content from a variety of sources and perform automatic summarization, tagging, and sentiment analysis – all without writing a single line of text-processing code or performing any sever-management tasks. This makes it possible to build web dashboards, in-app content analysis, or backend pipelines in mere hours.

Built For Developers

A simple, scalable API for machine intelligence

SAMPLE INPUT

var input = "https://news.ycombinator.com/rss";
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://tags/ScrapeRSS/0.1.6")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });

SAMPLE OUTPUT

[
  {
    "title": "Waitin' (on Leiningen)",
    "url": "http://swannodette.github.io/2014/12/22/waitin/",
    "description": "<a href=\"https://news.ycombinator.com/item?id=8790001\">Comments</a>"
  },
  {
    "title": "Daala progress update",
    "url": "https://people.xiph.org/~xiphmont/demo/daala/update1.shtml",
    "description": "<a href=\"https://news.ycombinator.com/item?id=8790468\">Comments</a>"
  }
]
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