Large scale opinion mining for social, news and blog data

Tsirakis, Nikos; Poulopoulos, Vassilis; Tsantilas, Panagiotis; Varlamis, Iraklis

doi:10.1016/j.jss.2016.06.012

Cited by 31 publications

(15 citation statements)

References 4 publications

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“…PaloPro by Tsirakis et al . [TPTV16] is a brand monitoring platform which conducts opinion mining of data streams from multiple social media and news sources. Its dashboard visualization includes line plots and bar charts representing polarity for specific topics or named entities.…”

Section: Sentiment Visualization Techniquesmentioning

confidence: 99%

“…The most popular choice by far is Colour , used by 89% of techniques. Most techniques that focus on polarity values use green for positive and red for negative polarity [WS08, TPTV16], although several techniques reverse this colour map to use green/blue as a cold hue corresponding to negative polarity, and orange/red for positive polarity [WFL*12, WFL*13, CAHF14, CFKA14, HC14, HC16, YWC*16]. The techniques related to emotions or affect categories other than positive/neutral/negative use either an ordinal set of colours representing categories [KR11 ZGWZ14, EAGA*16] or interpolate the colours based on the corresponding dimensional model [Alm13, WSK*15].…”

Section: Sentiment Visualization Techniquesmentioning

confidence: 99%

“…Polarity of individual tweets is visualized with stream graphs and geospatial heat maps, and a fine-grained analysis of emotions in the text data is available with a scatter plot representation. PaloPro by Tsirakis et al [TPTV16] is a brand monitoring platform which conducts opinion mining of data streams from multiple social media and news sources. Its dashboard visualization includes line plots and bar charts representing polarity for specific topics or named entities.…”

Section: Data Sourcementioning

confidence: 99%

See 2 more Smart Citations

The State of the Art in Sentiment Visualization

Kucher

Paradis

Kerren

2017

Computer Graphics Forum

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Section: Sentiment Visualization Techniquesmentioning

confidence: 99%

Section: Sentiment Visualization Techniquesmentioning

confidence: 99%

Section: Data Sourcementioning

confidence: 99%

See 1 more Smart Citation

The State of the Art in Sentiment Visualization

Kucher

Paradis

Kerren

2017

Computer Graphics Forum

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show abstract

“…According to Karthik Dinakar, [40], [3], cyberbullying is a more persistent version of traditional forms of intimidation, which extend beyond the physical confines of a school, sports field or workplace, with the victim often does not experience any respite from it. Cyberbullying gives an individual the power to embarrass or hurt a victim before an entire online community [41], especially in the realm of social networking websites. This is widely recognized as a serious social problem, [38], [40], [3], [42], [43], especially for teenagers.…”

Section: Cyberbullyingmentioning

confidence: 99%

Automatic Cyberbullying Detection in Spanish-language Social Networks using Sentiment Analysis Techniques

Mercado

Chuctaya

Gutierrez³

2018

ijacsa

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Cyberbullying is a growing problem in our society that can bring fatal consequences and can be presented in digital text for example at online social networks. Nowadays there is a wide variety of works focused on the detection of digital texts in the English language, however in the Spanish language there are few studies that address this issue. This paper aims to detect this cybernetic harassment in social networks, in Spanish language. Sentiment analysis techniques are used, such as bag of words, elimination of signs and numbers, tokenization and stemming, as well as a Bayesian classifier. The data used for the training of the Bayesian classifier were obtained from the Spanish Dictionary of Affect in Language (SDAL), which is a database formed by more than 2500 words manually evaluated in three affective dimensions: Pleasantness, activation and imagery, as well as same 595 words obtained following the same procedure of SDAL was used with the help of the members of the Research Center, Technology Transfer and Software Development. As a result, the software developed has 93% success in the validation tests carried out.

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“…Sentiment can be classified as feeling, emotion or opinion of a person towards something such as situation or events. Emotions constitute a key element in human instinct and behaviour as it can be communicated through different media, for example, speech, facial expressions, gestures and textual information [7]. Organizations that gather and break down information from social media, news and other information streams are confronted with a few difficulties that involve storing and handling of large amount of information.…”

Section: Introductionmentioning

confidence: 99%

Visualization of Crime News Sentiment in Facebook

Haron¹,

Abidin²,

Zamani³

et al. 2018

IJET

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Facebook has become a popular platform in communicating information. People can express their opinions using texts, symbols, pictures and emoticons via Facebook posts and comments. These expressions allow sentiment analysis to be performed by collecting the data to obtain the public's opinions and emotions toward certain issues. Due to a huge amount of data obtained from Facebook, proper approaches are required to cater the texts and symbols used in the comments. There are also limited amount of dictionary on Malay texts which make it more challenging to process and classify the positive and negative words used in the comments. Thus, hybrid approach is applied during the data processing to visualize the results. In this work, a combination of lexicon-based approach and Naïve Bayes are used. This study focuses on analyzing the public's sentiments on crime news in Facebook by using word cloud visualization. The visualization displays important words used in a form of a word cloud. Moreover, the percentage of positive and negative words existed in the comments is also shown as part of the visualization results.

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Large scale opinion mining for social, news and blog data

Cited by 31 publications

References 4 publications

The State of the Art in Sentiment Visualization

The State of the Art in Sentiment Visualization

Automatic Cyberbullying Detection in Spanish-language Social Networks using Sentiment Analysis Techniques

Visualization of Crime News Sentiment in Facebook

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