针对Twitter数据集缺失值的布尔型特征是否应设为默认值(False/0)？

Absolutely—you should fill those missing boolean values with False or 0, and here's why:

• Aligns with Twitter's native platform rules：Twitter’s system explicitly sets these boolean fields to False (or 0, depending on data export format) when a user doesn’t actively enable the feature. For example, if a user never turned on geo-tagging for their tweets, geo-enabled defaults to False; public accounts without protection have protected set to False by default. Missing values here almost always represent this default state, not some ambiguous edge case.

• Avoids analytical bias and data loss：Leaving missing values intact can mess up downstream work. Many analysis tools or machine learning models either exclude rows with nulls (wasting valuable samples) or treat missing entries as a separate category, introducing unnecessary noise. Filling with the default value keeps your dataset complete and true to actual user behavior.

• Guarantees data consistency：Standardizing these fields to pure boolean (0/1 or True/False) values eliminates type mismatches or unexpected glitches when running stats, visualizations, or model training. A consistent dataset is easier to work with and produces more reliable results.

A quick sanity check tip: If you’re worried about rare edge cases (like missing values from data collection errors instead of default states), check the proportion of missing entries. If it’s a tiny percentage, filling with defaults is totally safe. For larger missing subsets, you could cross-reference with related fields (e.g., see if users with missing geo-enabled have ever posted geo-tagged tweets) to confirm—but in most Twitter datasets, the default value is the correct call.

内容的提问来源于stack exchange，提问作者Reza