Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{159996,
        author = {Rakesh Kundu and Saraswat Ghosh and Shivam Shreyansh and Yash Yadav and Bhasker Rao},
        title = {Instagram Reach Analysis and Prediction},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {12},
        pages = {952-956},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159996},
        abstract = {An analysis of Instagram reach and prediction of future reach is an important topic in the field of social media marketing. Instagram, as one of the most popular social media platforms, has a significant impact on businesses and individuals looking to promote their products or personal brand. In this project, we propose to conduct an in-depth analysis of Instagram reach and develop a prediction model to forecast future reach. Instagram is a photo and video sharing social networking service. The app allows users to upload media that can be edited with filters and organized by hashtags and geographical tagging. Posts can be shared publicly or with preapproved followers. Users can browse other users' content by tag and location, view trending content, like photos, and follow other users to add their content to a personal feed. Data on a range of variables, including the number of followers, the nature of the content shared, the time of day, and the use of hashtags and hashtags, which may influence Instagram reach, will be gathered. In this paper we are discussing various methods applied to reach & predict the Instagram posts.},
        keywords = {Instagram, Prediction, Likes, Hashtags, Trends},
        month = {},
        }