Before starting, ensure you have the necessary tools installed. Install the AWS CLI and Google Cloud SDK on your local machine. Also, set up Python or another programming language that supports AWS and Google Cloud SDKs. Ensure you have the required permissions to access S3 and Google Pub/Sub.

Create an IAM user with necessary permissions to access your S3 bucket. Download the AWS access keys and configure them using the AWS CLI. Run `aws configure` and input your AWS Access Key ID, Secret Access Key, region, and output format.

Use the AWS SDK for Python (Boto3) to download data from your S3 bucket. Write a script to list the objects in your S3 bucket and download them locally. Here�s a basic example:
```python
import boto3
s3 = boto3.client('s3')
bucket_name = 'your-bucket-name'
for obj in s3.list_objects_v2(Bucket=bucket_name)['Contents']:
s3.download_file(bucket_name, obj['Key'], obj['Key'])
```
Ensure you handle exceptions and errors properly to manage large datasets.

Prepare your data for publishing to Google Pub/Sub. Depending on your data structure, you may need to transform or serialize it. Consider using JSON or another serialization format that suits your needs. This step may involve parsing the data to extract the necessary information.

Set up authentication for Google Cloud. Create a service account with Pub/Sub Publisher role, download the JSON key file, and set the `GOOGLE_APPLICATION_CREDENTIALS` environment variable to the path of this file. This allows your application to authenticate to Google Cloud services.

Use the Google Cloud Pub/Sub client library to publish the processed data. Initialize a Pub/Sub client and publish messages to your specified topic. Here�s a basic example using Python:
```python
from google.cloud import pubsub_v1
project_id = 'your-gcp-project-id'
topic_id = 'your-topic-id'
publisher = pubsub_v1.PublisherClient()
topic_path = publisher.topic_path(project_id, topic_id)
# Example data publishing
data = b'My data to publish'
future = publisher.publish(topic_path, data)
print(f'Published message ID: {future.result()}')
```
Ensure you handle any exceptions and log the results for debugging purposes.

Once your scripts are working correctly, automate the data transfer process. Use cron jobs or AWS Lambda to schedule regular data transfers. Implement logging and monitoring to track the success and failure of data transfers, ensuring you can react to any issues promptly.
This guide provides a basic framework to move data from S3 to Google Pub/Sub without third-party connectors. Adapt and expand upon these steps based on your specific requirements and data processing needs.