scholarly journals GIF Video Sentiment Detection Using Semantic Sequence

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Dazhen Lin ◽  
Donglin Cao ◽  
Yanping Lv ◽  
Zheng Cai
Keyword(s):  
Social Media ◽  
State Of The Art ◽  
The State ◽  
Middle Level ◽  
Semantic Gap ◽  
Classification Methods ◽  
Detection Approach ◽  
Semantic Concepts ◽  
Sentiment Detection ◽  
Media Applications

With the development of social media, an increasing number of people use short videos in social media applications to express their opinions and sentiments. However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. In this context, we propose a SentiPair Sequence based GIF video sentiment detection approach with two contributions. First, we propose a Synset Forest method to extract sentiment related semantic concepts from WordNet to build a robust SentiPair label set. This approach considers the semantic gap between label words and selects a robust label subset which is related to sentiment. Secondly, we propose a SentiPair Sequence based GIF video sentiment detection approach that learns the semantic sequence to understand the sentiment from GIF videos. Our experiment results on GSO-2016 (GIF Sentiment Ontology) data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art middle level sentiment ontology features, Adjective Noun Pairs (ANPs).

IT for Peace? Fighting Against Terrorism in Social Media – An Explorative Twitter Study

i-com ◽  
2017 ◽  
Vol 16 (2) ◽  
pp. 181-193 ◽  
Author(s):  
Christian Reuter ◽  
Katja Pätsch ◽  
Elena Runft
Keyword(s):  
Social Media ◽  
Information Systems ◽  
Empirical Study ◽  
State Of The Art ◽  
The State ◽  
The Internet ◽  
New Members ◽  
Starting Point ◽  
The Media

AbstractThe Internet and especially social media are not only used for supposedly good purposes. For example, the recruitment of new members and the dissemination of ideologies of terrorism also takes place in the media. However, the fight against terrorism also makes use of the same tools. The type of these countermeasures, as well as the methods, are covered in this work. In the first part, the state of the art is summarized. The second part presents an explorative empirical study of the fight against terrorism in social media, especially on Twitter. Different, preferably characteristic forms are structured within the scope with the example of Twitter. The aim of this work is to approach this highly relevant subject with the goal of peace, safety and safety from the perspective of information systems. Moreover, it should serve following researches in this field as basis and starting point.

scholarly journals Aspect Extraction from Bangla Reviews Through Stacked Auto-Encoders

Data ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 121
Author(s):  
Matteo Bodini
Keyword(s):  
State Of The Art ◽  
Classification Performance ◽  
The State ◽  
Automatic Process ◽  
Classification Methods ◽  
Aspect Extraction ◽  
Average Improvement ◽  
Art Works ◽  
Online Comments ◽  
Points Of View

Interactions between online users are growing more and more in recent years, due to the latest developments of the web. People share online comments, opinions, and reviews about many topics. Aspect extraction is the automatic process of understanding the topic (the aspect) of such comments, which has obtained huge interest from commercial and academic points of view. For instance, reviews available in webshops (like eBay, Amazon, Aliexpress, etc.) can help the customers in purchasing products and automatic analysis of reviews would be useful, as sometimes it is almost impossible to read all the available ones. In recent years, aspect extraction in the Bangla language has been regarded more and more as a task of growing importance. In the previous literature, a few methods have been introduced to classify Bangla texts according to the aspect they were focused on. This kind of research is limited mainly due to the lack of publicly available datasets for aspect extraction in the Bangla language. We take into account the only two publicly available datasets, recently published, collected for the task of aspect extraction in the Bangla language. Then, we introduce several classification methods based on stacked auto-encoders, as far as we know never exploited in the task of aspect extraction in Bangla, and we achieve better aspect classification performance with respect to the state-of-the-art: the experiments show an average improvement of 0.17 , 0.31 and 0.30 (across the two datasets), respectively in precision, recall and F1-score, reported in the state-of-the-art works that tackled the problem.

scholarly journals Asteroid Family Identification: History and State of the Art

2015 ◽  
Vol 10 (S318) ◽  
pp. 16-27 ◽  
Author(s):  
Zoran Knežević
Keyword(s):  
State Of The Art ◽  
The State ◽  
Classification Methods ◽  
Data Set ◽  
The Third ◽  
Proper Elements ◽  
The Future ◽  
History Of ◽  
Asteroid Families ◽  
Collisional Evolution

AbstractThe history of asteroid families, from their discovery back in 1918, until the present time, is briefly reviewed. Two threads have been followed: on the development of the theories of asteroid motion and the computation of proper elements, and on the methods of classification themselves. Three distinct periods can be distinguished: the first one until mid-1930s, devoted to discovery and first attempts towards understanding of the properties of families; the second one, until early 1980s, characterized by a growing understanding of their importance as key evidence of the collisional evolution; the third one, characterized by an explosion of work and results, comprises the contemporary era. An assessment is given of the state-of-the-art and possible directions for the future effort, focusing on the dynamical studies, and on improvements of classification methods to cope with ever increasing data set.

scholarly journals Pendekatan Dakwah Kontemporari Melalui Kesenian

2020 ◽  
Vol 21 (1) ◽  
pp. 134-148
Author(s):  
Ahmad Sahlan Abdul Hatim ◽  
Mohd Nizam Sahad
Keyword(s):  
Social Media ◽  
Communication Technology ◽  
Document Analysis ◽  
The State ◽  
Target Audience ◽  
Human Beings ◽  
Islamic Perspective ◽  
Traditional Approaches ◽  
Media Applications ◽  
Society Today

The development of da'wah demands a diverse approach in line with the passage of time and the state of society today. The delivery of preaching is no longer tied to lectures or traditional approaches but is even necessary to contemporary approaches that meet the demands of the target audience. Realizing that art has the values of beauty and can give charm to human beings, then the use of art in da'wah is quite significant. In addition to contributing to the demands of nature, art that meets Shari'a boundaries and contains educational elements also has the potential to influence thinking and lifestyle more positively. As such, art is seen as one of the effective mediums for propagating Islam to its target audience through the use of communication technology and social media applications. Therefore, the study by document analysis as well as the results of research in the form of books, journals, and papers discuss the concept of da'wah and art, art according to Islamic perspective and art as a contemporary da'wah approach. Perkembangan dakwah pada masa kini menuntut kepada pendekatan yang pelbagai selari dengan peredaran zaman dan keadaan masyarakat pada masa kini. Penyampaian dakwah tidak lagi terikat dengan cara berceramah atau pendekatan secara tradisi semata-mata bahkan perlu kepada pendekatan kontemporari yang dapat memenuhi keinginan sasaran dakwah. Menyedari kesenian yang mempunyai nilai-nilai keindahan dan berupaya memberi daya tarikan kepada manusia, maka pemanfaatan kesenian dalam dakwah adalah suatu yang cukup signifikan. Di samping berperanan memenuhi tuntutan fitrah, kesenian yang menepati batasan syariat serta mengandungi elemen-elemen mendidik turut berpotensi besar dalam mempengaruhi pemikiran dan gaya hidup ke arah yang lebih positif. Justeru, kesenian dilihat sebagai salah satu medium dakwah yang berkesan dalam menyebarluaskan Islam kepada sasaran khalayak melalui penggunaan aplikasi teknologi komunikasi dan media sosial. Oleh yang demikian, kajian secara analisis dokumen serta hasil kajian dalam bentuk buku, jurnal dan kertas kerja ini membincangkan tentang konsep dakwah dan kesenian, kesenian menurut perspektif Islam dan kesenian sebagai pendekatan dakwah kontemporari.

scholarly journals Interaction Strength Analysis to Model Retweet Cascade Graphs

2020 ◽  
Vol 10 (23) ◽  
pp. 8394
Author(s):  
Paola Zola ◽  
Guglielmo Cola ◽  
Michele Mazza ◽  
Maurizio Tesconi
Keyword(s):  
Social Media ◽  
Information Diffusion ◽  
State Of The Art ◽  
Interaction Strength ◽  
Diffusion Path ◽  
The State ◽  
Strength Analysis ◽  
Information Propagation ◽  
Original Message ◽  
Graph Generation

Tracking information diffusion is a non-trivial task and it has been widely studied across different domains and platforms. The advent of social media has led to even more challenges, given the higher speed of information propagation and the growing impact of social bots and anomalous accounts. Nevertheless, it is crucial to derive a trustworthy information diffusion graph that is capable of highlighting the importance of specific nodes in spreading the original message. The paper introduces the interaction strength, a novel metric to model retweet cascade graphs by exploring users’ interactions. Initial findings showed the soundness of the approaches based on this new metric with respect to the state-of-the-art model, and its ability to generate a denser graph, revealing crucial nodes that participated in the retweet propagation. Reliable retweet graph generation will enable a better understanding of the diffusion path of a specific tweet.

scholarly journals Understanding Media Communication: On the Significance of Iconic Thinking for a Praxeological Model of Communication

SAGE Open ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 215824402095206
Author(s):  
Aglaja Przyborski ◽  
Thomas Slunecko
Keyword(s):  
Qualitative Research ◽  
Social Media ◽  
Social Research ◽  
State Of The Art ◽  
The State ◽  
Self Presentation ◽  
Media Communication ◽  
Picture Analysis

This article outlines the state of the art in picture analysis as it has been developed in the trajectory of reconstructive methodology. Analyzing pictures in their own right—that is, by adhering to the particular affordances of the medium “picture”—has strong implications for qualitative research some of which are discussed in this article. With regard to content, this discussion revolves around questions pertaining to bodily self-presentation in mass and social media. On this basis, the article concludes with a praxeological model of communication that offers a guideline for social research which is clued-up as to its own media and, thus, takes into account that meaning in pictures is constructed differently than meaning in language.

scholarly journals Target-Aspect-Sentiment Joint Detection for Aspect-Based Sentiment Analysis

2020 ◽  
Vol 34 (05) ◽  
pp. 9122-9129
Author(s):  
Hai Wan ◽  
Yufei Yang ◽  
Jianfeng Du ◽  
Yanan Liu ◽  
Kunxun Qi ◽  
...  
Keyword(s):  
Sentiment Analysis ◽  
High Performance ◽  
State Of The Art ◽  
Language Model ◽  
The State ◽  
Experimental Results ◽  
Joint Detection ◽  
Sentiment Detection ◽  
Novel Method ◽  
The Given

Aspect-based sentiment analysis (ABSA) aims to detect the targets (which are composed by continuous words), aspects and sentiment polarities in text. Published datasets from SemEval-2015 and SemEval-2016 reveal that a sentiment polarity depends on both the target and the aspect. However, most of the existing methods consider predicting sentiment polarities from either targets or aspects but not from both, thus they easily make wrong predictions on sentiment polarities. In particular, where the target is implicit, i.e., it does not appear in the given text, the methods predicting sentiment polarities from targets do not work. To tackle these limitations in ABSA, this paper proposes a novel method for target-aspect-sentiment joint detection. It relies on a pre-trained language model and can capture the dependence on both targets and aspects for sentiment prediction. Experimental results on the SemEval-2015 and SemEval-2016 restaurant datasets show that the proposed method achieves a high performance in detecting target-aspect-sentiment triples even for the implicit target cases; moreover, it even outperforms the state-of-the-art methods for those subtasks of target-aspect-sentiment detection that they are competent to.

Altmetrics: an analysis of the state-of-the-art in measuring research impact on social media

2016 ◽  
Vol 109 (2) ◽  
pp. 1117-1166 ◽  
Author(s):  
Mojisola Erdt ◽  
Aarthy Nagarajan ◽  
Sei-Ching Joanna Sin ◽  
Yin-Leng Theng
Keyword(s):  
Social Media ◽  
State Of The Art ◽  
Research Impact ◽  
The State

scholarly journals Rumour prevention in social networks with layer 2 blockchains

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Subhasis Thakur ◽  
John G. Breslin
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
State Of The Art ◽  
Privacy Preserving ◽  
The State ◽  
Media Content ◽  
The Social ◽  
Layer 2 ◽  
Art Methods

AbstractSocial bots can cause social, political, and economical disruptions by spreading rumours. The state-of-the-art methods to prevent social bots from spreading rumours are centralised and such solutions may not be accepted by users who may not trust a centralised solution being biased. In this paper, we developed a decentralised method to prevent social bots. In this solution, the users of a social network create a secure and privacy-preserving decentralised social network and may accept social media content if it is sent by its neighbour in the decentralised social network. As users only choose their trustworthy neighbours from the social network to be part of its neighbourhood in the decentralised social network, it prevents the social bots to influence a user to accept and share a rumour. We prove that the proposed solution can significantly reduce the number of users who are share rumour.

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