Abstract
In today’s technological era, most new generations are using memes because the phenomenon of memes is rapidly gaining in popularity. In addition, various modifications and parodies use social and cultural phenomena to transform an original idea into another. Virus memes are sometimes called virus scripts and are the most widespread on the Internet. However, there is little scientific evidence for this assumption. This paper presents an innovative method to generate memes using machine learning algorithms that match the users’ humorous and relevant captions. The VGG16 network is used to return the embedded image. We have collected feedback from citizens of more than five countries and received 37 feedbacks to find humorous memes. The obtained results from feedback are very encouraging from the generated memes.
Highlights
When users utilize various social networking websites, they have various questions, such as which image they should upload on Facebook that is more eye-catching
The creation of memes was proved in this paper using several networks
The model includes a convolutional neural network encoder and an LSTM decoder to aid in sentence generation
Summary
When users utilize various social networking websites, they have various questions, such as which image they should upload on Facebook that is more eye-catching. These questions bother professionals and regular internet users.[1,2,3,4,5,6] The ability to reach and be recognized by many people determines the influence of marketing techniques, social causes, ads, political campaigns, non-profit organizations, authors, and photographers, to name a few. It is critical to determine whether pictures and media are transmitted through word of mouth.[1] Memes are one of the most popular forms of media among social media users. Google Insight gives weekly summaries based on how often a term/ query has been searched/used since January 1st, 2004, and enables geographic and category filtering
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