Research on the Correlation between Sentiment of Danmaku and the
Gift Value across Different Types of Live Streamers:
Dictionary-based Sentiment Analysis and Regression Test
Yuming Hu
a
Maastricht University, School of Business and Economics
Maastricht, Limburg, 6224 JT 5 a01, Netherlands
Keywords: Live Streaming, Live Streamers, Gift-Sending, Danmaku, Sentiment.
Abstract: Live streaming becomes more and more important as an entertaining method these days, and viewers can
interact with live streamers and others by sending gifts and sending danmaku. This paper had collected
1174040 pieces of danmaku data from 182 live streamers and the corresponding gift data from Huya TV from
Dec.7 to Dec. 23. The author investigated the relation between different types of sentiment of danmaku and
the gift value for entertaining live streamers and game live streamers collectively. To analyse sentiment of
danmaku, the sentiment dictionary made by Dalian University of Technology was adopted, and the regression
model was established to test the correlation. The results show that compliment is positively associated with
the gift value for entertaining live streamers while love and blame are positively correlated with the gift value
for game live streamers, but hatred is negatively associated with the gift value for game live streamers.
1 INTRODUCTION
Live streaming is a data transmission method used to
deliver a video file over the internet in real time
(Cloudfare 2021), and it allows anyone to share his or
her personal experience with the public at live events
(Lu, Xia, Heo, Wigdor 2018). According to Xinhua
net (Liu 2021), the number of live streaming users in
China in 2020 reached 0.617 billion. The market size
of worldwide video streaming industry was about 28
billion USD in 2020 (Live Streaming Market, 2021).
What is more, for the sake of real time, viewers could
interact with live streamers by sending danmaku, a
type of texts scrolling over the screen that every
viewer including live streamer could see, and by
sending valued gifts (Zhou, Zhou, Ding, Wang 2019).
With respect to the importance of gifts, several
figures can illustrate that (Platform Data of all live
streaming platforms in China, Toubang.tv 2021).
Ranked by net gift value in China, during September
2021, the top one live streamer received gifts worth
51 million CNY, the 100
th
live streamer received 3.5
million CNY; during October 2021, the top one live
a
https://orcid.org/0000-0001-8501-066X
streamer received 10 million CNY, and the 100th live
streamer received 2 million CNY.
This paper aims to dive deep into the relation
between sentiment of danmaku and gifts-giving
behaviours. Because sending danmaku and sending
gifts are major ways to interact with live streamers
and other viewers, and live streamers’ characteristics
will affect gift-giving intention (Li, Peng, 2021). This
paper argues that the pattern of emotion is distinct
among different types of live streamers and explores
their relationship on gift-giving behaviours.
Specifically, the research question is what types of
emotion can contribute to the gift value in
entertaining live streamer and game live streamers
respectively. In doing so, firstly, this paper will
introduce a different measurement of both sentiment
of danmaku and gift-giving behaviors compared to
the past literature. Secondly, this paper will propose
a carefully-designed data selection process. This
paper has several contributions to both past literature
and live streamers. First, it argues that the number of
gifts is not a good measurement of gift-giving
behaviours and instead, it adopts the gift value as a
proxy. Second, it analyses the correlation between
356
Hu, Y.
Research on the Correlation between Sentiment of Danmaku and the Gift Value across Different Types of Live Streamers Dictionary-based Sentiment Analysis and Regression Test.
DOI: 10.5220/0011178400003440
In Proceedings of the International Conference on Big Data Economy and Digital Management (BDEDM 2022), pages 356-360
ISBN: 978-989-758-593-7
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
different types of sentiment of danmaku and the gift
value while the past literature (Zhou, Ding, Wang,
2019) only took excitement-related emotion into
account. Third, it contributes to live streamers by
revealing that different kinds of live streamers should
be able to guide different sentiment pattern of
danmaku.
2 LITERATURE REVIEW
Previous literature researched gift-sending behaviors
through several lenses. Based on attachment theory
that a strong emotional bond between individuals and
a particular object can affect people’s gift-giving
intention (Ren, Harper, Drenner, Terveen, Kiesler,
Riedl, Kraut, 2012, Wan, Lu, Wang, Zhao, 2017), Li
and Peng (Li, Peng, 2021) researched the correlation
between live streamer characteristics and gift-giving
intention and the correlation between live scene
characteristics and gift-giving intention; their results
show that trustworthiness and attractiveness of live
streamers are positively associated with gift-giving
intention while the correlation between live scene
characteristics and gift-giving intention is not
significant. Li et al. (Li, Lu, Ma, Wang, 2021) studied
the impact of viewers’ identity on gift-giving
behaviours. Specifically, they explored class identity
and relational identity; viewers’ class identity was
measured by noble membership, a feature embedded
in live streaming platforms to distinguish viewers by
purchasing, and viewers’ relational identity was
measured by whether viewers wore fan badges;
results reveal that viewers’ class identity is positively
associated with the number of paid gifts and
negatively associated with the number of free gifts,
but relational identity is positively related with both
the number of paid gifts and free gifts. However, it is
remarkable that in most of live streaming platforms
in China, a fan badge is only worth 1 CNY, but
viewers can decide whose badge they take. In light of
social interaction theory that considers social
interaction an indispensable desire for human beings
(Baumeister, Leary, 1995), and that social interaction
can affect people’s behaviours (Castilla 2005, Rogers
2010), Zhou et al. (Zhou, Zhou, Ding, Wang, 2019)
investigated the association between danmaku and
the number of gifts, and found that the number of
words, the number of excitement-related words, the
similarity of danmaku, and debate level of danmaku
are positively associated with the gift value.
Nevertheless, it has several limitations. First, the
number of gifts is not a good measure for gift-giving
behaviours as differences among the gift value could
be extremely large. For example, the most expensive
gift in Huya TV (https://www.huya.com) is worth
5000 CNY while the cheapest gift is worth only 0.1
CNY. Second, it only counted the number of
excitement-related words, but words could have
different types of emotions such as happiness,
appraising, and peacefulness.
3 METHODOLOGY
3.1 Data Selection
This paper takes two factors into account in the
process of data selecting. Firstly, Zhu et al. (Zhu,
Yang, Dai, 2017) argue that most gifts in live
streaming platforms are channeled into a few live
streamers. It implies that if people want to research
gift-giving behaviors, they should focus on relatively
large live streamers as they are the most important.
Secondly, there is one thing that past literature
ignored but is important. That is the difference
regarding gift-giving behaviours among different
types of live streamers can be extremely large;
according to Toubang (Live streamers’ list ranked by
gifts value, https://www.toubang.tv), the average gift
value per live streamer in Beauties and star-show
section in China between Nov. 25 and Dec. 25 is 16
thousand CNY while the average gift value in League
of legends, Honour of kings, and Game for peace is
no more than 1 thousand CNY for each. In view of
these points, this paper crawled data of Huya TV
(http://huya.com) from Dec. 7 to December. 23. It is
one of the biggest live streaming platforms in China
and filters datafiles (every datafile is a collection of a
single live streamer) less than 100 kb. The 100 kb
criterion is determined arbitrarily, and the descriptive
information of the dataset will be given later.
The dataset contains the following features: the
live streamer’s ID, the type of channel, the gift name,
the gift number, and danmaku. As shown in Table 1,
182 examples were collected, and there are four types
of live streamers, Beauties and star-show, League of
legends, Honour of kings, and Game for peace.
Specifically, 60 observations are for Beauties and star
show, 44 observations are for League of legends, 42
examples are for Honour of kings, and 36 examples
are for Game for peace. Concerning the gift value and
danmaku number, examples from Beauties and star-
show had obtained 819817 CNY and 226220 pieces
of danmaku; examples from League of legends had
obtained 152947 CNY and 273592 pieces of
danmaku;
examples from Honour of kings had
Research on the Correlation between Sentiment of Danmaku and the Gift Value across Different Types of Live Streamers Dictionary-based
Sentiment Analysis and Regression Test
357
Table 1: Descriptive information of gift and danmaku.
Type of channels
live streamers’ numbe
r
Gift value
(
CNY
)
Pieces of danmaku
Beauties and star-show 60 819817 226220
League of legends 44 152947 273592
Honor of kings 42 235999 508051
Game for peace 36 121533 166177
Total 182 1330296 1174040
received 235999 CNY and 508051 pieces of
danmaku, and cases from Game for peace had gained
121533 CNY and 166177 pieces of danmaku.
3.2 Research Design
In order to analyse different types of sentiment for
Chinese danamku, this paper introduced a sentiment
dictionary made by Dalian University of
Technology(http://ir.dlut.edu.cn/info/1013/1142.htm
). It includes 27466 sentiment words of 6 major
sentiment types, happiness, praising, anger, sadness,
fear, hatred, and amazement, and these major
sentiment types can be extended into 21 sub-types.
For example, praising can be extended into respect,
compliment, trust, love, and wish. In the stage of data
cleaning, this paper adopted Jieba
(https://github.com/fxsjy/jieba) to tokenize Chinese
words. Moreover, this paper compared the proportion
of emotional words between Beauties and star show
and other types of live streamers, and ranked the most
common 4 types of sentiment. The proportion of a
specific type of sentiment is defined as the proportion
of the number of this type of sentiment to the number
of all emotional words. Table 2 shows that
compliment and blame are the most common
sentiment regardless of types of live streamers. In
three types of game live streamers, happiness is the
third most frequent sentiment, but in live streamers of
Beauties and star-show, love is the third most
frequent sentiment. What is more, this paper
categorized League of legends, Honour of kings, and
Game for peace into the game cluster and grouped
Beauties and star show into the entertaining cluster
.
Table 2: Comparison of different types of sentiment.
T
yp
e of channels 1st 2n
d
3r
d
4th
Beauties and sta
r
-show PH, 52% NN, 15% PB, 11% PA, 5%
Lea
ue of le
ends PH, 29% NN, 19% PA, 8% ND, 7%
Honor of kin
g
s PH, 31% NN, 18% PA, 9% ND, 8%
Game for peace PH, 48% NN, 12% PA, 10% PB, 8%
Note: PH indicates compliment-related words, NN indicates the number of blame-related words, PB indicates love-related
words, PA indicates happiness-related words, ND indicates hatred-related words
In light of these results, this paper constructed a
research model whose dependent variable is the
logarithm of the gift value to the base e and whose
independent variables include the number of
compliment-related words, the number of blame-
related words, the number of love-related words, the
number of happiness-related words, and the number
of hatred-related words.
ln
𝐺𝑖𝑓𝑡𝑠 =𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡+𝛽
∗𝑃𝐻+𝛽
∗𝑃𝐴+
+𝛽
∗𝑃𝐵+𝛽
∗𝑁𝑁+𝛽
𝑁𝐷 (1)
4 RESULT ANALYSIS
Table 3 shows the regression results of the impact of
different types of sentiment on the gift value. Panel 1
in Table 3 is regression results for entertaining live
streamers. The number of compliment-related words
is the only significant variable as its p-value is 4%
smaller than 5%. It indicates that compliment is the
only significant emotion out of five emotions for
entertaining live streamers because its p-value is
smaller than 5%. Its coefficient is 0.0008, which
means compliment is positively associated with the
gift value for entertaining live streamers, and every
additional compliment-related word will increase
0.08% of the gift value. Panel 2 in Table 3 is
regression results for game live streamers.
Significant variables include the number of love-
related words, the number of blame-related words,
and the number of hatred-related words as the p-value
is less than 5% for each. The coefficients of the
number of love-related words and the number of
BDEDM 2022 - The International Conference on Big Data Economy and Digital Management
358
blame-related words are 0.0045 and 0.0019,
respectively, which indicates that love and blame are
both positively correlated with the gift value received
by game live streamers. The coefficient of the number
of hatred-related words is -0.0038, which indicates
that hatred is negatively associated with the gift value
for game live streamers, and an additional hatred-
related word will decrease 0.38% of the gift value.
Table 3: Regression results for entertaining live streamers and game live streamers.
Panel 1
Entertaining live
s
treamers Panel 2
Game live
s
treamers
Coefficients
P
-value Coefficients
P
-value
Interce
p
t 7,6579 0,00 6,8857 0,00
PH 0,0008 0,04 -0,0003 0,45
PA 0,0028 0,24 0,0009 0,47
PB -0,0003 0,73 0,0045
0,03
NN 0,0004 0,39 0,0019 0,03
ND 0,0019 0,29 -0,0038 0,00
Note: PH indicates the number of compliment-related words, NN indicates the number of blame-related words, PB indicates
the number of love-related words, PA indicates the number of happiness-related words, ND indicates the number of hatred-
related words
According to the results, it is clear that the
importance of different types of sentiment is distinct
between entertaining live streamers and game live
streamers. What is the reason behind that? Li and
Peng (Li, Peng, 2021) argues that different
characteristics of live streamers have an impact on
gift-sending intention, but they did not state that
different characteristics of live streamers could lead
to different desired sentiment pattern regarding the
gift value In general, entertaining live streamers are
more attractive compared to game live streamers, but
game live streamers are more trustful compared to
entertaining live streamers because entertaining live
streamers exhibit themselves to viewers while game
live streamers exhibit the game content to viewers.
Though do not know the actual mechanism behind
that, this paper believes that different characteristics
of live streamers is the cause of different sentiment
patterns.
Regarding the positive coefficient of the number
of blame-related words for game live streamers, the
result is quite striking as intuitively the author
expected that to be negative. In real life, many
viewers send blame-related danmaku especially after
live streamers made some mistakes. To some extent,
viewers throw blame on game live streamers’
shoulders to show they really engage with them, and
hence it is positively associated with gifts value.
5 CONCLUSIONS
This paper examined the relationship between
different types of sentiment of danmaku and the gift
value for entertaining live streamers and game live
streamers. To conclude, different types of live
streamers require different sentiment patterns to
increase their gift value. Concerning entertaining live
streamers, compliment is positively associated with
the gift value. However, for game live streamers, love
and blame are positively related with the gift value,
but hatred is negatively related with the gift value.
This research has two important implications for
live streamers. First, live streamers should realize
their different characteristics compared to others.
Entertaining live streamers should try to exhibit their
attractiveness to viewers so as to make them express
compliment. Game live streamers should try their
best to earn viewers’ trust and make viewers love
them; meanwhile, game live streamers need to pay
special attention to hatred-related danmaku as it can
harm their gift value. Second, game live streamers
should know how to get along with blame-related
danmaku as the results show that blame is actually
positively associated with the gift value.
This research also has one implication for further
research. The dataset only includes two types of live
streamers and 182 examples. Though this can give
people a basic understanding of the research question,
a larger dataset might be better.
ACKNOWLEDGEMENT
Here, I would like to thank Qing Yin and Tianjiao
Yang for providing valuable ideas regarding the
structure and format of this paper.
Research on the Correlation between Sentiment of Danmaku and the Gift Value across Different Types of Live Streamers Dictionary-based
Sentiment Analysis and Regression Test
359
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