Alekhya Dabbiru

COURSE: IS 5320 – 02 WEB ANALYTICS

Tag: humans

  • Understanding Natural Language Processing

    The Natural Language Processing field exists as an artificial intelligence domain which enables computers to comprehend human language through its two functions, understanding and generating language. Machines can operate with text and speech through NLP because it enables them to work with these forms of communication in a manner that matches human understanding. The system uses computer science together with linguistics and machine learning to process language and uncover its hidden meanings. The technology powers all common tools which include chatbots, translation applications, voice assistants, and search engines through its ability to process natural language user inquiries and speech.

    NLP

    NLP exists to create a connection between human language communication and computer systems which handle information. The use of NLP technologies enables systems to achieve language pattern detection and entity recognition and sentiment analysis and contextually appropriate response generation. NLP includes multiple processes which start with tokenization and proceed through parsing and semantic analysis to enable computers to understand language better. The development of better machine learning models leads to stronger NLP capabilities which businesses now use to improve customer service and conduct data analysis and automate content processing tasks.

    working of NLP

    Sources:

    https://www.deeplearning.ai/resources/natural-language-processing

    https://www.geeksforgeeks.org/nlp/introduction-to-natural-language-processing-nlp

    https://toolmyai.com/natural-language-processingnlp-in-2024/

    https://mlarchive.com/data-science/the-ultimate-guide-to-natural-language-processing-nlp/

  • Homework 7 summary

    Time Log – time spent on other students’ sites (4 entries):

    Date: Feb 16, 2026 From: 8:10 pm To: 8:38 pm
    Date: Feb 16, 2026 From: 8:40 pm To: 9:12pm
    Date: Feb 20, 2026 From: 7:04 am To: 7:30 am
    Date: Feb 22, 2026 From: 6:40 am To: 7:15 am

    Essay I. Summary of your activities in your contents including new contents created (one paragraph). Provide all the hyperlinks (clickable) of new contents you have created this week.

    This week, I reorganized my site to make it easier to navigate and match the HW requirements: I switched from the Makao theme to Twenty Twenty-Four theme because Makao wouldn’t support the 3-level HWs menus the way I needed, then rebuilt the header/footer, fixed tag placement, and set up two menus, a general menu for Tech/My Life and a separate HWs menu that contains all homework pages. I also published two new posts: Gen Z: Balance Over Burnout on how Gen Z prioritizes boundaries and direct communication to avoid burnout and Sleep Over Doomscrolling on how late-night scrolling disrupts sleep and affects productivity/health.

    The hyperlinks:

    Sleep over Doomscrolling: http://52.12.113.25/2026/02/19/sleep-over-doomscrolling/

    Gen Z: Balance Over Burnout : http://52.12.113.25/2026/02/19/gen-z-balance-over-burnout/

    Essay II. Summary of your “Event” in GA4 (add a screenshot) (one paragraph)

    I set up my GA4 “event” using Google Tag Manager. First, I made the GA4 Configuration tag (Initialization – All Pages) so GA4 loads on every page. Then I created custom GA4 Event tags for my two new posts, Gen Z: Balance Over Burnout and Sleep Over Doomscrolling and, used page-view triggers so the event fires only when someone lands on those specific post URLs. After publishing, I tested it in Preview/Tag Assistant and checked GA4 Realtime to make sure my custom event names showed up, and  it worked and is tracking correctly.

    UPDATE: Unfortunately, my previous HW7 submission and related posts were lost due to an unexpected issue on the site. I am not sure how the posts were deleted, but I recreated the entire assignment, including the required posts, Google Tag Manager setup, GA4 events, and tag cloud plugin configuration.

    Essay III. Find and describe one of best use cases using custom events in GA4 (one paragraph)

    Custom events in GA4 are really useful for tracking how people actually move around a site, not just which pages they visit. One of the best use cases is setting up an event to record the menu clicks, like when someone clicks “Tech,” “My Life,” or specific HW links. This would help us understand what sections visitors are most interested in and whether the navigation structure is clear. It’s basically a way to measure real user behavior and improve the site layout based on data.

    Sources:

    https://vrushangpatel.com/2025/10/ga4-custom-events/

  • HW 8 summary

    Time Log Teams – time spent on other Teams’ sites(must have 3 entries or more):
    Date: Feb. 27, 2026 From: 9:47 pm To: 10:05 pm
    Date: Feb. 27, 2026 From: 9:54 pm To: 10:25 pm
    Date: Mar. 02, 2026 From: 7:08 pm To: 7:35 pm

    Time Log Students – time spent on other students’ sites (must have 3 entries or more):
    Date: Feb. 24, 2026 From: 4:10 pm To: 4:45 pm
    Date: Feb. 26, 2026 From: 5:55 pm To: 6:20 pm
    Date: Sat., Mar. 01, 2026 From: 2:00 pm To: 2:35 pm

    Essay I. Summary of your activities in your contents including new contents created (one paragraph). Provide all the hyperlinks (clickable) of new contents you have created this week.

    This week, I created two new posts called ‘AI Literacy’ and ‘LLMs’ under the TECH section and HW8 menus of my site. In the ‘AI Literacy’ post, I explained what AI literacy is and why it matters for students, especially because AI tools are becoming common in both school and work. In the ‘LLMs’ post, I gave a simple introduction to large language models, how they generate text, and why it is important to double check information instead of trusting everything they output. I also had a system issue where I lost my posts, data content, and comments from last week, so I had to redo HW7 again. After fixing that and rebuilding my content, I completed these two new posts for this week and added them to my menu for easy access.

    New post links:

    Why AI Literacy Matters for Students: http://52.12.113.25/2026/02/25/why-ai-literacy-matters-for-students/

    Introduction to Large Language Models (LLMs): http://52.12.113.25/2026/02/25/introduction-to-large-language-models-llms/

    Essay II. Summary of your “Thank you” event conversion (add screenshots) (one paragraph)

    For this homework 8, I have created a ‘Thank You’ page on my website and tracked it as a conversion in GA4. I set up a GA4 event tag in Google Tag Manager, connected it to the correct trigger so it fires when the Thank You page is visited, and tested everything in Preview mode to make sure it worked. After that, I checked GA4 Realtime to confirm the thank_you event was showing up, and then I marked it as a key event in GA4. This helped me understand how conversions are created and verified.

    THANK YOU PAGE LINK:

    http://52.12.113.25/thank-you-so-much-for-visiting/

    thank_you event

    Essay III. Summary of your “menu click” event conversion (add screenshots) (one paragraph)

    For the menu click event, I track when users click on the ‘AI Literacy’ link in my menu. I created a Click -Just Links trigger in Google Tag Manager and set the condition to fire when the Click Text contains AI literacy. Then, I built a GA4 event tag and connected it to that trigger. I tested everything using Preview mode to confirm the tag fired correctly.

    After that, I checked GA4 Realtime and confirmed that the menu_ai_literacy event was showing up, and marked it as a key event to track it as a conversion.

    menu_ai_literacy event

  • Introduction to Large Language Models (LLMs)

    Large Language Models, which is popularly known as LLMs, function as artificial intelligence systems that can read and write like humans. They require extensive text data for their training because the model needs to understand language patterns to create responses and solve problems and produce text and perform translation work and make original content.

    The understanding of information by LLMs differ from how humans comprehend the information. The system generates responses through word prediction that usually follows the training data patterns. Because of that, they can sound very confident even when the answer is incorrect. It is important to use these systems with caution because they can replicate existing biases from their training data. The introduction of AI tools to educational and professional environments makes it necessary to understand LLM functionality for responsible tool usage.

    Sources:

    https://www.ibm.com/think/topics/large-language-models

    https://teaminnovatics.com/blogs/large-language-models-llms-overview/

    https://blog.acer.com/en/discussion/1297/llms-the-key-to-unlocking-the-potential-of-ai