Filter Words in a List

The Filter Words in a List tool helps you quickly find or remove specific words from any text list using flexible matching criteria. Whether you’re cleaning datasets, organizing content by keywords, or searching for specific terms across large lists, this browser-based tool instantly filters your content based on the words you specify. Perfect for content managers, data analysts, and researchers who need to isolate or exclude specific words from their text data with precision control.

How to Use:

1. Enter your filter words in the filter box at the top. Type one word per line that you want to use for filtering your list.
2. Paste your list into the input box. Each line will be processed independently against your filter criteria.
3. Adjust options in the “Options” box to control how filtering works:
   • Case sensitive: Makes filtering distinguish between uppercase and lowercase letters.
   • Whole words only: Matches complete words rather than partial text within larger words.
   • Trim whitespace: Removes extra spaces before processing to ensure clean matches.
   • Min word length: Sets minimum character count for words to be considered in filtering.
4. Select a filter mode:
   • Include matches: Shows only items that exactly match your filter words.
   • Exclude matches: Shows only items that don’t match your filter words.
   • Contains any word: Shows items that contain any of your filter words anywhere within them.
5. Copy or export the result using the buttons below the output box.

As you adjust settings, the output updates automatically so you can experiment and see what works best for your filtering needs.

What Filter Words in a List Can Do:

This tool transforms overwhelming lists into focused results that show exactly the content you need to see or remove. You’ll quickly isolate specific terms, categories, or topics without manually scanning through hundreds of entries. The Filter Words in a List functionality brings powerful text processing capabilities to everyday content management tasks.

Content managers use it to extract all articles containing specific keywords or remove unwanted terms from publication lists. Customer service teams rely on it to filter support tickets by product names, issue types, or priority keywords mentioned in descriptions.

Researchers find it invaluable for processing survey responses, interview transcripts, or literature reviews where specific terminology indicates relevant content. The flexible matching options handle real-world data where exact matches might miss important variations.

E-commerce teams use it to filter product catalogs by brand names, categories, or features. The exclude mode helps remove discontinued items, test products, or inappropriate content from customer-facing lists.

The “Contains any word” mode proves particularly useful for content discovery where you’re looking for items that mention any of several related terms. This is perfect for finding all entries related to a topic area rather than exact keyword matches.

Data cleaning projects benefit from the precision controls that handle inconsistent capitalization, extra spaces, and partial word matches that often create false positives in simple text searches.

Example:

Starting with this product list:

Red Apple
Green Apple
Fresh Banana
Ripe Banana
Orange Juice
Apple Pie
Banana Bread
Cherry Tart
Apple Sauce
Grape Jelly
Banana Split
Orange Slices
Apple Cider
Strawberry Jam
Blueberry Muffin

With filter words set to “Apple” and “Banana”, using “Contains any word” mode, you’d see:

Red Apple
Green Apple
Fresh Banana
Ripe Banana
Apple Pie
Banana Bread
Apple Sauce
Banana Split
Apple Cider

This shows you found 9 items that contain either “Apple” or “Banana” anywhere in their text, filtering out the items with Cherry, Orange, Grape, Strawberry, and Blueberry that don’t match your criteria.

Filter Words in a List Table:

This table demonstrates different filtering modes and how they process various types of content with different matching criteria.

Common Use Cases:

You’ll find this tool essential whenever you need to process lists based on specific word criteria. Marketing teams use it to segment customer lists by interests, locations, or product preferences mentioned in their profiles. Content teams rely on it to organize articles, blog posts, or social media content by topic keywords.

It’s perfect for data quality assurance where you need to identify or remove entries containing specific terms that indicate errors, duplicates, or inappropriate content. Research teams use it to filter academic papers, survey responses, or interview data by relevant terminology.

Customer support departments find it valuable for categorizing tickets, filtering feedback by product names, or identifying urgent issues based on specific keywords in descriptions. The flexible matching options ensure you catch variations while avoiding false positives that waste time in manual review processes.