# Analyze an Exported WhatsApp Chat Paste an exported WhatsApp chat to count messages per person, busiest hours and days, and top words and emoji. Fully in-browser — nothing is uploaded. ## Run it - **CLI:** `gizza tool whatsapp-chat-analyzer "[2024-01-05, 21:07:33] Alice: Hey Bob 😂😂 how are you? [2024-01-05, 21:08:01] Bob: good thanks! www.example.com [2024-01-06, 09:16:10] Bob: nice 😂"` - **Web:** https://gizza.ai/tools/whatsapp-chat-analyzer/ - **Agents:** machine-readable descriptor (parameters JSON Schema) at https://gizza.ai/tools/whatsapp-chat-analyzer/tool.json ## Inputs - `chat` — Exported chat text _(field)_ - `date_format` — Date format _(field)_ - `top` — Top words / emoji to list _(field)_ - `min_word_length` — Minimum word length _(field)_ - `ignore_stopwords` — Ignore common filler words _(field)_ ## Output - Chat summary (text) ## Query parameters Open the tool pre-filled and auto-run via URL: - `chat` — Exported chat text - `date_format` — Date format - `top` — Top words / emoji to list - `min_word_length` — Minimum word length - `ignore_stopwords` — Ignore common filler words Example: `https://gizza.ai/tools/whatsapp-chat-analyzer/?chat=%5B2024-01-05%2C%2021%3A07%3A33%5D%20Alice%3A%20Hey%20Bob%20%F0%9F%98%82%F0%9F%98%82%20how%20are%20you%3F%0A%5B2024-01-05%2C%2021%3A08%3A01%5D%20Bob%3A%20good%20thanks%21%20www.example.com%0A%5B2024-01-06%2C%2009%3A16%3A10%5D%20Bob%3A%20nice%20%F0%9F%98%82&date_format=auto&top=10&min_word_length=3&ignore_stopwords=true` --- ## About this tool Paste the text from an exported WhatsApp chat and get a local, deterministic report: total messages, participants, media and link counts, messages per person, busiest hours and weekdays, and the most-used words and emoji. The parser handles the common iOS bracketed export format (`[2024-01-05, 21:07:33] Alice: ...`) and the Android dash format (`05/01/2024, 21:07 - Alice: ...`). Multi-line messages are folded into the message above them, system notices are skipped, and media placeholders such as `` are counted without treating the placeholder as chat text. Example input: ```text [2024-01-05, 21:07:33] Alice: Hey Bob 😂😂 how are you? [2024-01-05, 21:08:01] Bob: good thanks! www.example.com [2024-01-06, 09:15:00] Alice: image omitted [2024-01-06, 09:16:10] Bob: nice 😂 ``` Useful limits and edge cases: - Ambiguous numeric dates can be auto-detected, forced to day/month/year, forced to month/day/year, or parsed as year-month-day for ISO exports. - `Top words / emoji to list` accepts `0` for every ranked entry; very large chats may produce long reports when this is set to `0`. - Emoji counting groups skin tones, flag pairs, variation selectors, and family-style ZWJ emoji sequences as single emoji tokens. - This is a text-export analyzer. It counts media placeholders from the export text; it does not inspect a WhatsApp `.zip` attachment bundle or read images, audio, or videos. ## FAQ
How do I get the chat text to paste here? Use WhatsApp's chat export feature and choose the text export. Open the exported `_chat.txt` or `.txt` file, copy the contents, and paste them into the text box. The tool runs in your browser and does not upload the chat.
Which WhatsApp export formats are supported? The analyzer supports iOS-style bracketed lines such as `[2024-01-05, 21:07:33] Alice: ...` and Android-style dash lines such as `05/01/2024, 21:07 - Alice: ...`. It also handles common AM/PM times, invisible direction marks, and continuation lines.
Why can the date format change the busiest day result? Dates like `05/01/2024` are ambiguous: they can mean 5 January or May 1. Leave the setting on auto for most exports, or choose day/month/year or month/day/year if you know how the export was written.
Does this read images, videos, or voice notes from a WhatsApp ZIP? No. It analyzes the text export only. Media placeholders are counted as media messages, but attachments themselves are not opened or inspected.
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