Double Texting Calculator: Who Sends Again Before a Reply?

For each pair of consecutive parsed messages, Textopsy checks whether the sender is the same. If so, it adds one consecutive-send event for that person. The other person’s reply ends that sequence.

There is no minimum wait in the current rule. Two messages one second apart count in the same way as a follow-up several hours later. The metric therefore measures message sequencing, not persistence after rejection.

Fictional sequence: Alex sends “Hey”, “Friday still good?”, and “I can book dinner.” Jordan then replies “Yes, 7 works.” Alex has 3 messages and 2 consecutive-send events: the second and third messages arrived before Jordan’s response.

If Jordan later sends two messages before Alex answers, Jordan gets 1 event. A run of n messages from one person contributes n minus 1 events; it does not mean there were n separate unanswered requests.

Some people send every thought in a separate bubble. Others write one long paragraph. Logistics, corrected typos, and live conversation can produce a high consecutive-send count without an effort imbalance.

Compare the count with total message volume and word share. Someone who sends most of the messages can naturally have more consecutive sends even when both people are equally engaged.

Check whether follow-ups repeatedly chase an unanswered direct question, whether only one person restarts the conversation, and whether that arrangement feels okay to you. Those observations are more useful than the raw count alone.

A practical question is “Do I keep sending because I have more to say, or because I rarely get an answer?” Review actual exchanges rather than making the other person pass a numerical test.

Export a two-person WhatsApp chat Without Media and upload the .txt or .zip to Textopsy. The free preview compares activity for both participants; the optional paid report adds interpretation and sampled examples.

Textopsy does not automatically distinguish a normal multi-part message from an anxious follow-up. Use the same counting rule for both people and bring your own context to the result.