Social media mining | Solutional Webdesign Antwerpen

TOUS 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Médias sociaux^[3] mining is a multifaceted process that involves gathering and analyzing data from various social media platforms. This data can include various types of content like social networking, photo sharing, news aggregation, or messagerie instantanée^[2]. The purpose of social media mining is to identify patterns or trends in the interactions and behaviors of social media users. These patterns can then be used by organizations to design strategies, launch new programs, or introduce new products. However, it also involves challenges such as handling large data sets and removing irrelevant information. These processes require knowledge from various fields including ordinateur^[5] science and statistics. As technologie^[4] advances, social media mining is expected to evolve and become more integrated with fields like intelligence artificielle^[1]. Ethical concerns, particularly around vie privée^[6], are expected to grow in importance in the future. Research in this field is vast, encompassing topics like public health monitoring and network measures.

Définitions des termes

1. ↑ intelligence artificielle.

1 Artificial Intelligence (AI) refers to the field of computer science that aims to create systems capable of performing tasks that would normally require human intelligence. These tasks include reasoning, learning, planning, perception, and language understanding. AI draws from different fields including psychology, linguistics, philosophy, and neuroscience. The field is prominent in developing machine learning models and natural language processing systems. It also plays a significant role in creating virtual assistants and affective computing systems. AI applications extend across various sectors including healthcare, industry, government, and education. Despite its benefits, AI also raises ethical and societal concerns, necessitating regulatory policies. AI continues to evolve with advanced techniques such as deep learning and generative AI, offering new possibilities in various industries.

2 Artificial Intelligence, commonly known as AI, is a field of computer science dedicated to creating intelligent machines that perform tasks typically requiring human intellect. These tasks include problem-solving, recognizing speech, understanding natural language, and making decisions. AI is categorised into two types: narrow AI, which is designed to perform a specific task, like voice recognition, and general AI, which can perform any intellectual tasks a human being can do. It's a continuously evolving technology that draws from various fields including computer science, mathematics, psychology, linguistics, and neuroscience. The core concepts of AI include reasoning, knowledge representation, planning, natural language processing, and perception. AI has wide-ranging applications across numerous sectors, from healthcare and gaming to military and creativity, and its ethical considerations and challenges are pivotal to its development and implementation.

2. ↑ messagerie instantanée. Instant Messaging (IM) is a digital communication method that enables real-time transmission of text-based messages over internet or computer networks. Unlike email, IM facilitates immediate, interactive conversation, often enhanced with emojis, file transfers, voice-over IP, and video chat. IM systems can function independently or as part of a larger social media platform. They have evolved significantly since early systems like Talkomatic and CompuServe CB Simulator, developing into graphical user interfaces with a wide range of features. Today's popular services, including Signal, Telegram, WhatsApp, and Snapchat, offer private and group messaging, advanced security measures such as end-to-end encryption, and integration with social networks. They play a vital role in both personal communication and business environments, facilitating effective real-time communication with conversation records for future reference.

Articles connexes :

Glossaire

Exploration des médias sociaux (Wikipedia)

Cet article présente plusieurs problèmes. Aidez-nous l'améliorer ou discuter de ces questions sur le site page de discussion. (Apprenez comment et quand supprimer ces messages du modèle)

Cet article is missing information about social media mining itself. Please expand the article to include this information. Further details may exist on the page de discussion. (August 2018)

Cet article may contain unverified ou indiscriminate l'information à embedded lists. Aidez-nous clean up the lists by removing items or incorporating them into the text of the article. (August 2018)

(Comment et quand supprimer ce modèle de message)

Exploration des médias sociaux is the process of obtaining big data de contenu généré par l'utilisateur on social media sites and mobile apps in order to extract actionable patterns, form conclusions about users, and act upon the information, often for the purpose of advertising to users or conducting research. The term is an analogy to the resource extraction process of mining for rare minerals. Resource extraction mining requires mining companies to shift through vast quantities of raw ore to find the precious minerals; likewise, social media mining requires human data analysts and automated software programs to shift through massive amounts of raw social media data in order to discern patterns and trends relating to social media usage, online behaviours, sharing of content, connections between individuals, online buying behaviour, and more. These patterns and trends are of interest to companies, governments and not-for-profit organizations, as these organizations can use these patterns and trends to design their strategies or introduce new programs, new products, processes or services.

Social media mining uses a range of basic concepts from computer science, data mining, machine learning et statistics. Social media miners develop algorithms suitable for investigating massive files of social media data. Social media mining is based on theories and methodologies from l'analyse des réseaux sociaux, network science, sociology, ethnography, optimization and mathematics. It encompasses the tools to formally represent, measure and model meaningful patterns from large-scale social media data. In the 2010s, major corporations, governments and not-for-profit organizations engaged in social media mining to obtain data about customers, clients and citizens.

" Retour à l'index des glossaires