[et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_fullwidth_image src=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2023\/08\/Multilingual-Sentiment-Analysis-of-Social-Media-Data-on-Extraction.jpg” alt=”Multilingual Sentiment Analysis of Social Media Data Extraction” _builder_version=”4.19.5″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][\/et_pb_fullwidth_image][\/et_pb_section][et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.18.0″ _module_preset=”default” custom_margin=”2px||0px||false|false” global_colors_info=”{}”][et_pb_fullwidth_post_title meta=”off” featured_image=”off” _builder_version=”4.18.0″ _module_preset=”default” title_text_align=”left” custom_margin=”0px||||false|false” custom_padding=”30px||||false|false” global_colors_info=”{}”][\/et_pb_fullwidth_post_title][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.18.0″ _module_preset=”default” custom_padding=”25px||||false|false” global_colors_info=”{}”][et_pb_row module_class=”inner-page” _builder_version=”4.18.0″ _module_preset=”default” custom_padding=”0px||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.19.5″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
A leading social media company which has revolutionized the way we all <\/span>purchase goods\u00a0utilizing cloud technology and Automatic Speech Recognition.<\/span><\/p>\n Our client wanted us to establish a process with minimum human intervention for categorizing social media posts based on brand relevancy and sentiment associated with it, that would save time and resources.<\/p>\n Service:<\/strong>\u00a0Software Development<\/span> Our client wanted us to create a tool that would collect all social media posts relevant to a specific product and brand. The tool would need to be able to extract posts from multiple languages like, German, French, Spanish, and Japanese . These posts would then be categorized according to their relevance and sentiment.<\/p>\n Fidel analyzed the requirements for extracting social media data and categorizing its contents. He identified key areas that play an important role in this process, including:<\/p>\n Based on this analysis, Fidel laid out a flow to achieve audio signal processing using technology and programming languages like Python and its NumPy library. This flow makes it easy to use NLP to process audio signals.<\/p>\n <\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Section” module_class=”footer-cnt” _builder_version=”4.19.5″ _module_preset=”default” background_color=”#103e66″ custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” locked=”off” global_colors_info=”{}”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.17.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.17.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.19.5″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n If you found this case study similar to your requirement OR interested to get our services, please connect with us using form. We will be happy to respond.<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.19.5″ _module_preset=”default” global_colors_info=”{}”]<\/span><\/p>\nRequirements :<\/h2>\n
Project details:<\/h2>\n
\nSource language:\u00a0<\/span><\/strong>English
\nTarget language:\u00a0<\/span><\/strong>German, French, Spanish, and Japanese.
\nTools and technology used: <\/span><\/strong>\u00a0Python<\/span><\/p>\nChallenges :<\/h2>\n
Solution :<\/h2>\n
\n
Result :<\/h2>\n
\n
Is this Case Study interests you?<\/h2>\n
<\/i>Call us<\/h3>\n