To use a custom lexicon with the VADER sentiment analysis tool, you need to ensure that the tool recognizes and loads your custom lexicon correctly. Here are the steps you can follow:

1. Modify sentiment_analyzer.py to Use Custom Lexicon:

Open the sentiment_analyzer.py file and look for the part where it loads the VADER lexicon. This is usually done using the SentimentIntensityAnalyzer class from the nltk.sentiment module.

Replace the line that loads the VADER lexicon with the path to your custom lexicon:

```
from nltk.sentiment import SentimentIntensityAnalyzer

# Load your custom lexicon
custom_lexicon_path = “/path/to/your/custom_lexicon.txt”
sia = SentimentIntensityAnalyzer(lexicon_file=custom_lexicon_path)
```

Ensure that the lexicon_file parameter points to the correct path of your custom lexicon file.

1. Ensure Correct Lexicon Format:

Make sure that your custom lexicon file has the same format as the VADER lexicon. Each line should contain a word followed by its polarity score, tab-separated.

Example:

word1 0.5 word2 -0.3

1. Check Lexicon Loading:

After modifying sentiment_analyzer.py, you can add some debug prints to ensure that the custom lexicon is loaded. For example:

```
from nltk.sentiment import SentimentIntensityAnalyzer

# Load your custom lexicon
custom_lexicon_path = “/path/to/your/custom_lexicon.txt”
sia = SentimentIntensityAnalyzer(lexicon_file=custom_lexicon_path)

print(“Loaded custom lexicon from:”, custom_lexicon_path)
```

Run your script and check if the print statement shows the correct path.

1. Ensure NLTK Data Path:

Sometimes, NLTK might be using a different data path. You can explicitly set the data path in your script:

```
import nltk

nltk.data.path.append(“/path/to/nltk_data”)
```

Make sure to replace “/path/to/nltk_data” with the actual path where NLTK data is located.

After making these changes, run your script and check if it now uses your custom lexicon for sentiment analysis. If you are using NLTK as part of a larger application, ensure that these changes are reflected in the relevant part of your code.