The Experts below are selected from a list of 1893 Experts worldwide ranked by ideXlab platform
Ricardo Soto - One of the best experts on this subject based on the ideXlab platform.
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facilitating analysis of Audience Reaction on social networks using content analysis a case study based on political corruption
International Conference on Human-Computer Interaction, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
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HCI (27) - Facilitating Analysis of Audience Reaction on Social Networks Using Content Analysis: A Case Study Based on Political Corruption
HCI International 2016 – Posters' Extended Abstracts, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
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towards the easy analysis of mass media Audience Reaction on social networks via discursive category tools
International Conference on Human-Computer Interaction, 2015Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick CrawfordAbstract:The Mass Media involves information and communication products targeted to a wide Audience. Today such communications products are also available on Internet where people can react to a given information by posting critics, congratulations, opinions or whatever they want via social networks. Such Reactions are considered valuable information for instance to government and companies. However, this information is hard to automatically process as people commonly use ironies, stereotypes, metaphors expressed in informal writing plenty of chat abbreviations, emoticons, and slang words. In this paper, we illustrate how tools based on discursive categories can be used to analyze such Reactions and thus to process and understand the information behind them.
Eduardo Olguin - One of the best experts on this subject based on the ideXlab platform.
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facilitating analysis of Audience Reaction on social networks using content analysis a case study based on political corruption
International Conference on Human-Computer Interaction, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
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HCI (27) - Facilitating Analysis of Audience Reaction on Social Networks Using Content Analysis: A Case Study Based on Political Corruption
HCI International 2016 – Posters' Extended Abstracts, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
Stefanie Niklander - One of the best experts on this subject based on the ideXlab platform.
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facilitating analysis of Audience Reaction on social networks using content analysis a case study based on political corruption
International Conference on Human-Computer Interaction, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
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HCI (27) - Facilitating Analysis of Audience Reaction on Social Networks Using Content Analysis: A Case Study Based on Political Corruption
HCI International 2016 – Posters' Extended Abstracts, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
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towards the easy analysis of mass media Audience Reaction on social networks via discursive category tools
International Conference on Human-Computer Interaction, 2015Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick CrawfordAbstract:The Mass Media involves information and communication products targeted to a wide Audience. Today such communications products are also available on Internet where people can react to a given information by posting critics, congratulations, opinions or whatever they want via social networks. Such Reactions are considered valuable information for instance to government and companies. However, this information is hard to automatically process as people commonly use ironies, stereotypes, metaphors expressed in informal writing plenty of chat abbreviations, emoticons, and slang words. In this paper, we illustrate how tools based on discursive categories can be used to analyze such Reactions and thus to process and understand the information behind them.
Broderick Crawford - One of the best experts on this subject based on the ideXlab platform.
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facilitating analysis of Audience Reaction on social networks using content analysis a case study based on political corruption
International Conference on Human-Computer Interaction, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
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HCI (27) - Facilitating Analysis of Audience Reaction on Social Networks Using Content Analysis: A Case Study Based on Political Corruption
HCI International 2016 – Posters' Extended Abstracts, 2016Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick Crawford, Claudio Leon De La Barra, Eduardo OlguinAbstract:Today, once a political corruption case takes place, it is rapidly viralized along the Internet where people can react by posting their opinions through social networks. Such Audience Reaction is clearly interesting but complex to analyze as people employs stereotypes, metaphors, and ironies expressed in an informal language hard to interpret. In this paper, we present how content analysis can help us to uncover the hidden meaning of a message. We focus here on the automated analysis of two political corruption cases and its corresponding opinions through social networks. In particular, one case involves the current government while the second one mostly involves the opposite side. Interesting results are gathered where the use of Content Analysis allows us to easily process the social network information in order to provide clear feedback.
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towards the easy analysis of mass media Audience Reaction on social networks via discursive category tools
International Conference on Human-Computer Interaction, 2015Co-Authors: Stefanie Niklander, Ricardo Soto, Broderick CrawfordAbstract:The Mass Media involves information and communication products targeted to a wide Audience. Today such communications products are also available on Internet where people can react to a given information by posting critics, congratulations, opinions or whatever they want via social networks. Such Reactions are considered valuable information for instance to government and companies. However, this information is hard to automatically process as people commonly use ironies, stereotypes, metaphors expressed in informal writing plenty of chat abbreviations, emoticons, and slang words. In this paper, we illustrate how tools based on discursive categories can be used to analyze such Reactions and thus to process and understand the information behind them.
Manish Singh - One of the best experts on this subject based on the ideXlab platform.
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Toward Maximizing the Visibility of Content in Social Media Brand Pages: A Temporal Analysis
arXiv: Social and Information Networks, 2019Co-Authors: Nagendra Kumar, Gopi Ande, J. Shirish Kumar, Manish SinghAbstract:A large amount of content is generated everyday in social media. One of the main goals of content creators is to spread their information to a large Audience. There are many factors that affect information spread, such as posting time, location, type of information, number of social connections, etc. In this paper, we look at the problem of finding the best posting time(s) to get high content visibility. The posting time is derived taking other factors into account, such as location, type of information, etc. In this paper, we do our analysis over Facebook pages. We propose six posting schedules that can be used for individual pages or group of pages with similar Audience Reaction profile. We perform our experiment on a Facebook pages dataset containing 0.3 million posts, 10 million Audience Reactions. Our best posting schedule can lead to seven times more number of Audience Reactions compared to the average number of Audience Reactions that users would get without following any optimized posting schedule. We also present some interesting Audience Reaction patterns that we obtained through daily, weekly and monthly Audience Reaction analysis.
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Toward maximizing the visibility of content in social media brand pages: a temporal analysis
Social Network Analysis and Mining, 2018Co-Authors: Nagendra Kumar, Gopi Ande, Jessu Shirish Kumar, Manish SinghAbstract:A large amount of content is generated everyday in social media. One of the main goals of content creators is to spread their information to a large Audience. There are many factors that affect information spread, such as posting time, location, type of information, number of social connections. In this paper, we look at the problem of finding the best posting time(s) to get high content visibility. The posting time is derived taking other factors into account, such as location, type of information. In this paper, we do our analysis over Facebook pages. We propose six posting schedules that can be used for individual pages or group of pages with similar Audience Reaction profile. We perform our experiment on a Facebook pages dataset containing 0.3 million posts, 10 million Audience Reactions. Our best posting schedule can lead to seven times more number of Audience Reactions compared to the average number of Audience Reactions that users would get without following any optimized posting schedule. We also present some interesting Audience Reaction patterns that we obtained through daily, weekly and monthly Audience Reaction analysis.
