{
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    "title": "News Sentiment Analyzer",
    "description": "Analyze news articles for sentiment using NLP. Extract positive, negative, and neutral signals from any news URL or keyword-based news feed.",
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  "components": {
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        "type": "object",
        "properties": {
          "query": {
            "title": "Search Query",
            "type": "string",
            "description": "Search query — company name, ticker symbol, topic, or keyword phrase. Leave empty to use 'queries' array instead.",
            "default": "technology news"
          },
          "queries": {
            "title": "Multiple Queries",
            "type": "array",
            "description": "Run multiple queries in a single actor run. Each query gets its own sentiment summary. If both 'query' and 'queries' are provided, 'query' is prepended to the list.",
            "items": {
              "type": "string"
            }
          },
          "sources": {
            "title": "News Sources",
            "type": "array",
            "description": "Which news sources to scrape. Google News and Bing News provide the broadest coverage for most queries.",
            "items": {
              "type": "string"
            },
            "default": [
              "google_news",
              "bing_news"
            ]
          },
          "maxArticlesPerQuery": {
            "title": "Max Articles Per Query",
            "minimum": 1,
            "maximum": 500,
            "type": "integer",
            "description": "Maximum number of articles to scrape and analyze per query. Higher values give more data but take longer to run.",
            "default": 50
          },
          "language": {
            "title": "Language",
            "type": "string",
            "description": "Language code for news results (ISO 639-1). Used to filter news to a specific language.",
            "default": "en"
          },
          "country": {
            "title": "Country",
            "type": "string",
            "description": "Country code for regional news results (ISO 3166-1 alpha-2). Affects which regional news appears in results.",
            "default": "US"
          },
          "dateRange": {
            "title": "Date Range",
            "enum": [
              "1d",
              "3d",
              "7d",
              "14d",
              "30d",
              "90d"
            ],
            "type": "string",
            "description": "How far back to look for articles. Shorter ranges give more current sentiment; longer ranges show trends.",
            "default": "7d"
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          "sentimentModel": {
            "title": "Sentiment Model",
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              "pattern"
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            "description": "Sentiment analysis model to use. 'afinn' is faster (word-level scoring). 'pattern' is slower but considers sentence structure.",
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          "extractEntities": {
            "title": "Extract Named Entities",
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            "description": "Extract named entities (people, companies, locations) from articles and include per-entity sentiment scores.",
            "default": true
          },
          "extractTopics": {
            "title": "Extract Topics",
            "type": "boolean",
            "description": "Extract and cluster key topics and themes across articles. Useful for identifying what's driving sentiment.",
            "default": true
          },
          "includeArticleText": {
            "title": "Include Full Article Text",
            "type": "boolean",
            "description": "Include the full extracted article text in each output item. Increases dataset size significantly — only enable if you need the raw text.",
            "default": false
          },
          "minArticleLength": {
            "title": "Minimum Article Length",
            "minimum": 0,
            "maximum": 5000,
            "type": "integer",
            "description": "Minimum character length for an article to be analyzed. Articles shorter than this are saved to the dataset with a ARTICLE_TOO_SHORT error and no sentiment score.",
            "default": 100
          },
          "groupBySource": {
            "title": "Group By Source",
            "type": "boolean",
            "description": "Include a per-source sentiment breakdown in the run summary (stored in the Key-Value Store as OUTPUT).",
            "default": true
          },
          "groupByDate": {
            "title": "Group By Date",
            "type": "boolean",
            "description": "Include a daily sentiment time-series in the run summary. Shows how sentiment is trending over time.",
            "default": true
          },
          "proxyConfiguration": {
            "title": "Proxy Configuration",
            "type": "object",
            "description": "Proxy settings for scraping news sources. Datacenter proxy is sufficient for most news sites.",
            "default": {
              "useApifyProxy": true
            }
          }
        }
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                "type": "string",
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                "example": "2025-01-08T00:00:00.000Z"
              },
              "finishedAt": {
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              "status": {
                "type": "string",
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              "meta": {
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                    "type": "string",
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                  "userAgent": {
                    "type": "string"
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                }
              },
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                    "type": "integer",
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                    "type": "string",
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                    "type": "integer",
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