A Sentiment Analysis Tool for Determining the Promotional Success of Fashion Images on Instagram

Information

Goals

Meta

Result

Author

Dahab Galal

Mohamed AbdelFattah

Nada Hassan

Doaa S. Elzanfaly

Greg Tallent

Year

2017

This study focuses on analysing the reactions generated by the top 50 fashion houses on Instagram given their top 20 images with the highest number of likes

The basic question asked in this paper is whether there are certain visual aesthetics that appeal more to the user and are therefore more successful on social media than others as determined by a measure we introduce, ‘Social Value’. To do so, a sentiment analysis tool is developed to measure the proposed social value of each image.

Objective

Qualify the visual aesthetics of fashion images and to establish why some succeed on social media more than others.

Determine whether there are certain visual aesthetics that appeal more to the user and are therefore more successful on social media than others as determined by a measure we introduce, ‘Social Value’.

Sentiment Analysis

Phase

Lexicon phase

Adding to these results, the number of likes and shares would also be taken into consideration quantifying the image’s value. A cumulative result is then produced to determine the social value of an image

The output of the lexicon is a score value assigned to each comment to identify its degree of positivity, negativity, or it has no effect on the social value

The main purpose of this paper is to propose an application that can produce the social value/impact of a brand in the market through Instagram.

Data will be collected about the brand from the images uploaded by the brand.

Sentiment analysis will be applied on these images to identify the impact of each image has on the brand, then accumulate the whole social value as one result.

Image Evaluator

Pre-processing phase

Stem the words and remove any emojis, punctuations, or spaces

SNLP

Secondly we will use the tool to tag each word with its part of speech

As stated before, each brand has a set of images from which we
extracted the comments

The score of the image is defined by the accumulative score of all the comments related to the image over the total comments related to the image.

Brand Evaluator

The final component is responsible of outputting the final social value of each brand

After the module has evaluated each image in the previous component, in this component we get the average of the image scores related to the brand using equation

Literature Review

Data will be collected about the brand from the images uploaded by the brand. Sentiment analysis will be applied on these images to identify the impact of each image has on the brand, then accumulate the whole social value as one result.