IGNOU MNM 033 SOLVED ASSIGNMENT

Included:

MNM 033 2025 - English

MNM 033: DATA SCIENCE AND BIG DATA

September 2025 / March 2026

(Due Date: Please check the University website for the latest update on the due date)

Assignment Code: MNM033/Jan&July25

Maximum Marks: 100

Weightage: 30%

Note: Answer all the questions. All questions carry equal marks 20 each Attempt each question in about 500 words.

1. You are working in a digital newsroom during a general election. How would you use real-time data on audience engagement (clicks, shares, comments) to guide story updates and editorial decisions throughout the day? Mention relevant data tools and ethical concerns.

2. A national media outlet assigns you to investigate disparities in healthcare access. Describe how you would use data mining and visualisation to uncover patterns in public health records. How can such an approach strengthen investigative journalism?

3. Many mobile news apps offer personalised content based on what users read, watch, or search for. As a media researcher, how would you study audience behaviour using data from such an app (e.g., time spent on articles, categories browsed, or frequency of visits)? What patterns would you look for to understand user preferences, and how could this help improve the content shown to different users?

4. As part of a digital media research project, you aim to study misinformation trends during a major public health event. How would you use social media data and sentiment analysis to identify and classify misinformation?

5. Reflect on how learning data science tools (like data cleaning, visualisation, and analytics) can help journalism students better understand audience behaviour in the digital age. Give examples of tools and their practical application in content creation.

MNM 033 (January 2025 - July 2025) - ENGLISH

MNM 033: DATA SCIENCE AND BIG DATA

September 2025 / March 2026

(Due Date: Please check the University website for the latest update on the due date)

Assignment Code: MNM033/Jan&July25

Maximum Marks: 100

Weightage: 30%

Note: Answer all the questions. All questions carry equal marks = 20 each

Attempt each question in about 500 words.

1. You are working in a digital newsroom during a general election. How would you use real-time data on audience engagement (clicks, shares, comments) to guide story updates and editorial decisions throughout the day? Mention relevant data tools and ethical concerns.

2. A national media outlet assigns you to investigate disparities in healthcare access. Describe how you would use data mining and visualisation to uncover patterns in public health records. How can such an approach strengthen investigative journalism?

3. Many mobile news apps offer personalised content based on what users read, watch, or search for. As a media researcher, how would you study audience behaviour using data from such an app (e.g., time spent on articles, categories browsed, or frequency of visits)? What patterns would you look for to understand user preferences, and how could this help improve the content shown to different users?

4. As part of a digital media research project, you aim to study misinformation trends during a major public health event. How would you use social media data and sentiment analysis to identify and classify misinformation?

5. Reflect on how learning data science tools (like data cleaning, visualisation, and analytics) can help journalism students better understand audience behaviour in the digital age. Give examples of tools and their practical application in content creation.

MNM 033 (January 2026 - July 2026) - ENGLISH

MNM033: DATA SCIENCE AND BIG DATA

September 2026 / March 2027

(Due Date: Please check the University website for the latest update on the due date)

Assignment Code: MNM033

January 2026 / July 2026

Maximum Marks: 100

Weightage: 30%

Note: Answer all the questions. All questions carry equal marks = 20 each Attempt each question in about 500 words

1. Observe how a digital news app or website personalises content for you. Analyse the benefits of personalised news and discuss concerns related to privacy, filter bubbles, and limited viewpoints, drawing on your experience as an audience member.

2. Explore the public features of tools like Google Analytics or social media insights. Explain how such data helps newsrooms understand audience behaviour and shape content decisions, with examples from digital news platforms.

3. Identify one data-related skill used in journalism. Explain how this skill strengthens reporting and credibility. Mention any tool or software and describe how it supports evidence-based journalism.

4. Assume you are reporting on urban environmental pollution. Explain how data collection, basic analysis, and visual storytelling can help identify patterns and communicate findings clearly to the public.

5. Observe how news recommendations appear on a digital platform you use. Analyse how user data, such as clicks, reading history, or time spent, influences content suggestions. Discuss one ethical concern related to algorithm-driven news delivery.

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