A Case Study on Analysis of Facebook Posts of Different Bangladeshi Newspapers radio news to follow various occasions across the universe. Likewise, the creation, distribution and use of information are no longer the same as in the pre-innovation era, when people relied only on news media available twenty-four hours a day -four. However, at present, an increasing number of people looking for information are continually going online to learn about the most recent incidents around the world. Social media is rapidly changing the media scene in the recent context of information creation and dissemination. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get the original essay Nowadays, with the rapid pace of globalization influencing every aspect of life and disrupting data innovation that has fundamentally changed the procedure of information generation and its dispersion. Currently, all Internet users can without much difficulty engage in a global stage where information is freely accessible and easily disseminated to others. To define the term "social media" in accordance with Wikipedia, Wikipedia refers to the fact that social media are online-based innovations that allow users to share different and different information, thoughts, interests, and types of articulation via virtual networks. Facebook, LinkedIn and Twitter are some of the popular social networking and communication sites that allow their users to stay in touch with the sites by updating text, image, video or status. It is undeniable that the conventional norms of media practices and journalism are being changed due to the interactive aspect and important role of social media in communication and breaking news. The information provided by social media sites is almost in a textual format which is considered unstructured text. . Text mining is particularly used to bring out undefined and practical patterns or information from a sum of huge and unstructured data or corpora. Computational linguistics, information retrieval (IR) and data mining are research areas that are integrated by one of the branches of data mining called text mining, the researchers said. A good number of text mining techniques such as “topic detection and tracking, keyword extraction, sentiment analysis, document clustering and automatic document summarization” have been introduced to increase the effectiveness of text analysis. Furthermore, NPL is a field correlated with text mining that is concerned with the mutual relationships between a large amount of existing unstructured text. The generation of information and consumption of user-generated content has made the recent media debate a possible area of research. MotivationBangla has become one of the most widely spoken languages in the world. A good number of Bengali posts are shared daily on the Facebook pages of different Bangladeshi newspapers. Bengali language texts are unstructured and need to be transformed into informative knowledge from a large amount of data through the application of various text mining techniques. Due to thelack of literature on the analysis of Bengali texts, to be more specific about Bengali news, the present study seeks to explore the analysis model of Bengali textual newspapers that exist on social media. The main reason that prompted me to start my research is the availability of a large quantity of Bengali texts which I wish to transform into constructive knowledge.BackgroundThe motive of a background study is to help the current research to study. This is a first research step in designing a thesis because there are many questions to address and thoughts to clarify. All existing relevant works have been carried out through different text mining techniques belonging to this section along with the scopes and challenges. A growing number of readers and writers are successively attracted to social media, several researchers have revealed. The defining feature of a wide range of web-based social networks is their attractive quality and overall reputation among the global village internet users. Due to the global development of social media, for example Facebook, mass media is now outdated, it is now only personal media. It is quite undeniable that social networking sites like Facebook have one of the most popular contemporary news sources, where users have access to newspapers' Facebook pages and have the opportunity to choose whatever they want read or not. Basically, what we online users do when we go online is select the type of news or views that really interest us the most. A survey examined different text mining techniques to analyze the text pattern of social network as well as online applications. A survey revealed that the targeted authors provide a vast insight into different text mining techniques and their exercises on social sites. Classification and clustering are two of the key recently developed approaches to text mining in the intellectual analysis of unstructured text. A recent study was done on text mining and analysis, a case study that analyzed unstructured English text from different news channels on Facebook posts. The study showed several techniques for analyzing ambiguous raw data sets and transforming them into quantifiable data. The research relied on an integrated tool used to collect Facebook data and the analysis process was carried out by RapidMiner, an integrated environment for data science operations. By paying special attention to the "Arab Spring", examined during this vital phase of history, Facebook intends to collect practical details. on the feelings of online users. Based on Support Vector Machine (SVM) and Naïve Bayes, analysts used a system for this purpose. Furthermore, a lexical resource for sentiment analysis is created, extracted from emoticons, interjections and acronyms derived from users' status updates. Although the research came up with in-depth conclusions about the January 2011 Tunisian Revolution of Tunisian Facebook users, which is one of their recorded moments, it has some flaws identified with the changing emotions of the targeted users on one point accurate. The investigation did not take the time factor into account during the review and exchange, which did not completely influence the conclusions. If the study had included the time-related feature in its investigation, it would have been more fascinating. A small research was directed to investigate the enormous

Essay / A Case Study on Analysis of Facebook Posts of Different Bangladeshi Newspapers radio news to follow various occasions across the universe. Likewise, the creation, distribution and use of information are no longer the same as in the pre-innovation era, when people relied only on news media available twenty-four hours a day -four. However, at present, an increasing number of people looking for information are continually going online to learn about the most recent incidents around the world. Social media is rapidly changing the media scene in the recent context of information creation and dissemination. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get the original essay Nowadays, with the rapid pace of globalization influencing every aspect of life and disrupting data innovation that has fundamentally changed the procedure of information generation and its dispersion. Currently, all Internet users can without much difficulty engage in a global stage where information is freely accessible and easily disseminated to others. To define the term "social media" in accordance with Wikipedia, Wikipedia refers to the fact that social media are online-based innovations that allow users to share different and different information, thoughts, interests, and types of articulation via virtual networks. Facebook, LinkedIn and Twitter are some of the popular social networking and communication sites that allow their users to stay in touch with the sites by updating text, image, video or status. It is undeniable that the conventional norms of media practices and journalism are being changed due to the interactive aspect and important role of social media in communication and breaking news. The information provided by social media sites is almost in a textual format which is considered unstructured text. . Text mining is particularly used to bring out undefined and practical patterns or information from a sum of huge and unstructured data or corpora. Computational linguistics, information retrieval (IR) and data mining are research areas that are integrated by one of the branches of data mining called text mining, the researchers said. A good number of text mining techniques such as “topic detection and tracking, keyword extraction, sentiment analysis, document clustering and automatic document summarization” have been introduced to increase the effectiveness of text analysis. Furthermore, NPL is a field correlated with text mining that is concerned with the mutual relationships between a large amount of existing unstructured text. The generation of information and consumption of user-generated content has made the recent media debate a possible area of research. MotivationBangla has become one of the most widely spoken languages in the world. A good number of Bengali posts are shared daily on the Facebook pages of different Bangladeshi newspapers. Bengali language texts are unstructured and need to be transformed into informative knowledge from a large amount of data through the application of various text mining techniques. Due to thelack of literature on the analysis of Bengali texts, to be more specific about Bengali news, the present study seeks to explore the analysis model of Bengali textual newspapers that exist on social media. The main reason that prompted me to start my research is the availability of a large quantity of Bengali texts which I wish to transform into constructive knowledge.BackgroundThe motive of a background study is to help the current research to study. This is a first research step in designing a thesis because there are many questions to address and thoughts to clarify. All existing relevant works have been carried out through different text mining techniques belonging to this section along with the scopes and challenges. A growing number of readers and writers are successively attracted to social media, several researchers have revealed. The defining feature of a wide range of web-based social networks is their attractive quality and overall reputation among the global village internet users. Due to the global development of social media, for example Facebook, mass media is now outdated, it is now only personal media. It is quite undeniable that social networking sites like Facebook have one of the most popular contemporary news sources, where users have access to newspapers' Facebook pages and have the opportunity to choose whatever they want read or not. Basically, what we online users do when we go online is select the type of news or views that really interest us the most. A survey examined different text mining techniques to analyze the text pattern of social network as well as online applications. A survey revealed that the targeted authors provide a vast insight into different text mining techniques and their exercises on social sites. Classification and clustering are two of the key recently developed approaches to text mining in the intellectual analysis of unstructured text. A recent study was done on text mining and analysis, a case study that analyzed unstructured English text from different news channels on Facebook posts. The study showed several techniques for analyzing ambiguous raw data sets and transforming them into quantifiable data. The research relied on an integrated tool used to collect Facebook data and the analysis process was carried out by RapidMiner, an integrated environment for data science operations. By paying special attention to the "Arab Spring", examined during this vital phase of history, Facebook intends to collect practical details. on the feelings of online users. Based on Support Vector Machine (SVM) and Naïve Bayes, analysts used a system for this purpose. Furthermore, a lexical resource for sentiment analysis is created, extracted from emoticons, interjections and acronyms derived from users' status updates. Although the research came up with in-depth conclusions about the January 2011 Tunisian Revolution of Tunisian Facebook users, which is one of their recorded moments, it has some flaws identified with the changing emotions of the targeted users on one point accurate. The investigation did not take the time factor into account during the review and exchange, which did not completely influence the conclusions. If the study had included the time-related feature in its investigation, it would have been more fascinating. A small research was directed to investigate the enormous

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