TY - GEN

T1 - Negative A/Effect: Sentiment of French-Speaking Users and Its Impact Upon Affective Hashtags on Charlie Hebdo

AU - Бодрунова, Светлана Сергеевна

AU - Блеканов, Иван Станиславович

AU - Кукаркин, Михаил Михайлович

AU - Журавлева, Нина Николаевна

N1 - Conference code: 5th

PY - 2018/10

Y1 - 2018/10

N2 - Studies of user sentiment on social networks like Twitter have formed a steadily growing research area. But there is still lack of knowledge on whether the discussion clusters tagged by emotionally opposite hashtags differ in sentiment distribution, both in terms of difference between hashtags and between user types, e.g. non-influencers and influential accounts. We look at two hashtags that marked the discussion on the Charlie Hebdo massacre of 2015, namely #jesuischarlie and #jenesuispascharlie. As sentiment analysis studies for the French language are rare, we elaborate our own approach to sentiment vocabulary. We apply human coding and machine learning to correct the automated sentiment assessment. Then we apply the enhanced knowledge on sentiment to both discussion segments and compare the configuration of the resulting sentiment-based nebulae in overall and francophone-only discussions. Also, we define influencers for both discussions and compare whether ordinary and institutional users differ by sentiment. We have three notable findings. First, negativity structures #jenesuispascharie more than #jesuischarlie. Second, while francophones communicate cross-sentiment inside the francophone talk, their negativity tends to cast impact upon cluster formation inside general discussions. Third, influencers in both cases tend to be more negative than positive, but institutional users bear neutral and positive sentiment more than ordinary people.

AB - Studies of user sentiment on social networks like Twitter have formed a steadily growing research area. But there is still lack of knowledge on whether the discussion clusters tagged by emotionally opposite hashtags differ in sentiment distribution, both in terms of difference between hashtags and between user types, e.g. non-influencers and influential accounts. We look at two hashtags that marked the discussion on the Charlie Hebdo massacre of 2015, namely #jesuischarlie and #jenesuispascharlie. As sentiment analysis studies for the French language are rare, we elaborate our own approach to sentiment vocabulary. We apply human coding and machine learning to correct the automated sentiment assessment. Then we apply the enhanced knowledge on sentiment to both discussion segments and compare the configuration of the resulting sentiment-based nebulae in overall and francophone-only discussions. Also, we define influencers for both discussions and compare whether ordinary and institutional users differ by sentiment. We have three notable findings. First, negativity structures #jenesuispascharie more than #jesuischarlie. Second, while francophones communicate cross-sentiment inside the francophone talk, their negativity tends to cast impact upon cluster formation inside general discussions. Third, influencers in both cases tend to be more negative than positive, but institutional users bear neutral and positive sentiment more than ordinary people.

KW - Charlie Hebdo

KW - French

KW - Influencer

KW - Sentiment analysis

KW - Twitter

KW - Charlie Hebdo; Cluster formations; French; Influe

KW - Data mining; Learning systems; Social networking (

UR - https://link.springer.com/chapter/10.1007/978-3-030-01437-7_18

UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055833171&doi=10.1007%2F978-3-030-01437-7_18&partnerID=40&md5=68472ff27787d420ea74f604821deada

UR - http://www.mendeley.com/research/negative-aeffect-sentiment-frenchspeaking-users-impact-upon-affective-hashtags-charlie-hebdo

U2 - 10.1007/978-3-030-01437-7_18

DO - 10.1007/978-3-030-01437-7_18

M3 - Conference contribution

SN - 978-3-030-01436-0

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 226

EP - 241

BT - Internet Science - 5th International Conference, INSCI 2018, Proceedings

A2 - Bodrunova, Svetlana S.

PB - Springer Nature

T2 - 5th International Conference on Internet Science, INSCI 2018

Y2 - 24 October 2018 through 26 October 2018

ER -